Add support for latest versions of h5py, sympy, numpy, and pytest

.travis.yml

@@ -29,10 +29,11 @@ before_install:
   - export PYENV_ROOT="$HOME/.pyenv"
   - export PATH="$HOME/.pyenv/bin:$PATH"
   - eval "$(pyenv init -)"
-  - pyenv install -s 3.5.5
-  - pyenv install -s 3.6.5
-  - pyenv install -s 3.7.1
-  - pyenv local 3.5.5 3.6.5 3.7.1
+  - pyenv install -s 3.5.7
+  - pyenv install -s 3.6.9
+  - pyenv install -s 3.7.5
+  - pyenv install -s 3.8.0
+  - pyenv local 3.5.7 3.6.9 3.7.5 3.8.0
   - pip install tox tox-pyenv codecov twine
 
 # Command to run tests, e.g. python setup.py test

docs/usage.rst

@@ -1057,7 +1057,7 @@ HDF5 Files
 
 The :mod:`unyt` library provides a hook for writing data both to a new HDF5 file and an existing file and then subsequently reading that data back in to restore the array. This works via the :meth:`unyt_array.write_hdf5 <unyt.array.unyt_array.write_hdf5>` and :meth:`unyt_array.from_hdf5 <unyt.array.unyt_array.from_hdf5>` methods. The simplest way to use these functions is to write data to a file that does not exist yet:
 
-  >>> from unyt import cm, unyt_array
+  >>> from unyt import cm
   >>> import os
   >>> data = [1, 2, 3]*cm
   >>> data.write_hdf5('my_data.h5')

tox.ini

@@ -1,24 +1,26 @@
 [tox]
-envlist = py36-docs,begin,py35-dependencies,py35-versions,py{35,36,37},end
+envlist = py36-docs,begin,py35-dependencies,py35-versions,py{35,36,37,38},end
 
 [travis]
 python =
+    3.8: py38
     3.7: py37
     3.6: py36, py36-docs
     3.5: py35, py35-dependencies, py35-versions
 
 [testenv]
 setenv =
     PYTHONPATH = {toxinidir}
+recreate = true
 depends = begin
 deps =
-    pytest<5.1
+    pytest
     sympy
     numpy
     h5py
     pint
     astropy
-    coverage
+    coverage<5.0
     pytest-cov
     pytest-doctestplus
     flake8
@@ -30,13 +32,13 @@ commands =
 
 [testenv:py35-versions]
 deps =
-    pytest<5.1
+    pytest
     sympy==1.2
     numpy==1.13.3
     h5py==2.6.0
     pint==0.6
     astropy==1.3.3
-    coverage
+    coverage<5.0
     pytest-cov
     pytest-doctestplus
 commands =
@@ -46,10 +48,10 @@ commands =
 
 [testenv:py35-dependencies]
 deps =
-    pytest<5.1
+    pytest
     sympy
     numpy
-    coverage
+    coverage<5.0
     pytest-cov
     pytest-doctestplus
 depends = begin
@@ -77,13 +79,13 @@ commands =
 depends =
 skip_install = true
 deps =
-    coverage
+    coverage<5.0
 
 [testenv:end]
 commands =
     coverage report --omit='.tox/*'
     coverage html --omit='.tox/*'
 skip_install = true
-depends = py{35,36,37}
+depends = py{35,36,37,38}
 deps =
-    coverage
+    coverage<5.0

unyt/_parsing.py

@@ -76,7 +76,7 @@ def _auto_positive_symbol(tokens, local_dict, global_dict):
     "sqrt": sqrt,
 }
 
-unit_text_transform = (_auto_positive_symbol, rationalize, auto_number)
+unit_text_transform = (_auto_positive_symbol, auto_number, rationalize)
 
 
 def parse_unyt_expr(unit_expr):

unyt/array.py

@@ -127,8 +127,13 @@
 from unyt.equivalencies import equivalence_registry
 from unyt._on_demand_imports import _astropy, _pint
 from unyt._pint_conversions import convert_pint_units
+from unyt._unit_lookup_table import default_unit_symbol_lut
 from unyt.unit_object import _check_em_conversion, _em_conversion, Unit
-from unyt.unit_registry import _sanitize_unit_system, UnitRegistry
+from unyt.unit_registry import (
+    _sanitize_unit_system,
+    UnitRegistry,
+    default_unit_registry,
+)
 
 NULL_UNIT = Unit()
 POWER_SIGN_MAPPING = {multiply: 1, divide: -1}
@@ -321,6 +326,8 @@ def _sanitize_units_convert(possible_units, registry):
 
 trigonometric_operators = (sin, cos, tan)
 
+multiple_output_operators = {modf: 2, frexp: 2, divmod_: 2}
+
 LARGE_INPUT = {4: 16777217, 8: 9007199254740993}
 
 
@@ -1317,12 +1324,16 @@ def write_hdf5(self, filename, dataset_name=None, info=None, group_name=None):
             info = {}
 
         info["units"] = str(self.units)
-        info["unit_registry"] = np.void(pickle.dumps(self.units.registry.lut))
+        lut = {}
+        for k, v in self.units.registry.lut.items():
+            if k not in default_unit_registry.lut:
+                lut[k] = v
+        info["unit_registry"] = np.void(pickle.dumps(lut))
 
         if dataset_name is None:
             dataset_name = "array_data"
 
-        f = h5py.File(filename)
+        f = h5py.File(filename, "a")
         if group_name is not None:
             if group_name in f:
                 g = f[group_name]
@@ -1372,15 +1383,17 @@ def from_hdf5(cls, filename, dataset_name=None, group_name=None):
         if dataset_name is None:
             dataset_name = "array_data"
 
-        f = h5py.File(filename)
+        f = h5py.File(filename, "r")
         if group_name is not None:
             g = f[group_name]
         else:
             g = f
         dataset = g[dataset_name]
         data = dataset[:]
         units = dataset.attrs.get("units", "")
-        unit_lut = pickle.loads(dataset.attrs["unit_registry"].tostring())
+        unit_lut = default_unit_symbol_lut.copy()
+        unit_lut_load = pickle.loads(dataset.attrs["unit_registry"].tostring())
+        unit_lut.update(unit_lut_load)
         f.close()
         registry = UnitRegistry(lut=unit_lut, add_default_symbols=False)
         return cls(data, units, registry=registry)
@@ -1584,18 +1597,29 @@ def __getitem__(self, item):
     def __array_ufunc__(self, ufunc, method, *inputs, **kwargs):
         func = getattr(ufunc, method)
         if "out" not in kwargs:
-            out = None
-            out_func = None
+            if ufunc in multiple_output_operators:
+                out = (None,) * multiple_output_operators[ufunc]
+                out_func = out
+            else:
+                out = None
+                out_func = None
         else:
             # we need to get both the actual "out" object and a view onto it
             # in case we need to do in-place operations
-            out = kwargs.pop("out")[0]
-            if out.dtype.kind in ("u", "i"):
-                new_dtype = "f" + str(out.dtype.itemsize)
-                float_values = out.astype(new_dtype)
-                out.dtype = new_dtype
-                np.copyto(out, float_values)
-            out_func = out.view(np.ndarray)
+            out = kwargs.pop("out")
+            if ufunc in multiple_output_operators:
+                out_func = []
+                for arr in out:
+                    out_func.append(arr.view(np.ndarray))
+                out_func = tuple(out_func)
+            else:
+                out = out[0]
+                if out.dtype.kind in ("u", "i"):
+                    new_dtype = "f" + str(out.dtype.itemsize)
+                    float_values = out.astype(new_dtype)
+                    out.dtype = new_dtype
+                    np.copyto(out, float_values)
+                out_func = out.view(np.ndarray)
         if len(inputs) == 1:
             # Unary ufuncs
             inp = inputs[0]
@@ -1775,6 +1799,14 @@ def __array_ufunc__(self, ufunc, method, *inputs, **kwargs):
                 except AttributeError:
                     # out_arr is an ndarray
                     out.units = Unit("", registry=self.units.registry)
+            elif isinstance(out, tuple):
+                for o, oa in zip(out, out_arr):
+                    if o is None:
+                        continue
+                    try:
+                        o.units = oa.units
+                    except AttributeError:
+                        o.units = Unit("", registry=self.units.registry)
         if mul == 1:
             return out_arr
         return mul * out_arr

unyt/tests/test_unyt_array.py

@@ -1010,7 +1010,10 @@ def unary_ufunc_comparison(ufunc, a):
 
 
 def binary_ufunc_comparison(ufunc, a, b):
-    out = b.copy()
+    if ufunc in [np.divmod]:
+        out = (b.copy(), b.copy())
+    else:
+        out = b.copy()
     if ufunc in yield_np_ufuncs(
         [
             "add",
@@ -1073,7 +1076,10 @@ def binary_ufunc_comparison(ufunc, a, b):
     ):
         assert not isinstance(ret, unyt_array) and isinstance(ret, np.ndarray)
     if isinstance(ret, tuple):
-        assert_array_equal(ret[0], out)
+        assert isinstance(out, tuple)
+        assert len(out) == len(ret)
+        for o, r in zip(out, ret):
+            assert_array_equal(r, o)
     else:
         assert_array_equal(ret, out)
     if ufunc in (np.divide, np.true_divide, np.arctan2) and (
@@ -1353,6 +1359,10 @@ def test_astropy():
 
 
 def test_pint():
+    def assert_pint_array_equal(arr1, arr2):
+        assert_array_equal(arr1.magnitude, arr2.magnitude)
+        assert str(arr1.units) == str(arr2.units)
+
     if isinstance(_pint.UnitRegistry, NotAModule):
         return
     ureg = _pint.UnitRegistry()
@@ -1365,13 +1375,11 @@ def test_pint():
     yt_quan = unyt_quantity(10.0, "sqrt(g)/mm**3")
     yt_quan2 = unyt_quantity.from_pint(p_quan)
 
-    assert_array_equal(p_arr, yt_arr.to_pint())
-    assert_equal(p_quan, yt_quan.to_pint())
+    assert_pint_array_equal(p_arr, yt_arr.to_pint())
     assert_array_equal(yt_arr, unyt_array.from_pint(p_arr))
     assert_array_equal(yt_arr, yt_arr2)
 
-    assert_equal(p_quan.magnitude, yt_quan.to_pint().magnitude)
-    assert_equal(p_quan, yt_quan.to_pint())
+    assert_pint_array_equal(p_quan, yt_quan.to_pint())
     assert_equal(yt_quan, unyt_quantity.from_pint(p_quan))
     assert_equal(yt_quan, yt_quan2)
 
@@ -1477,7 +1485,7 @@ def test_h5_io():
 
     # write to a group that does exist
 
-    with _h5py.File("test.h5") as f:
+    with _h5py.File("test.h5", "a") as f:
         f.create_group("/arrays/test_group")
 
     warr.write_hdf5(

unyt/unit_object.py

@@ -87,7 +87,7 @@ def _get_latex_representation(expr, registry):
     l_expr = expr
     if isinstance(expr, Mul):
         coeffs = expr.as_coeff_Mul()
-        if coeffs[0] == 1 or not isinstance(coeffs[0], Float):
+        if coeffs[0] == 1 or not isinstance(coeffs[0], Number):
             l_expr = coeffs[1]
         else:
             l_expr = coeffs[1]