Fix continuous integration

.github/workflows/main.yml

@@ -2,49 +2,22 @@ name: Continuous Integration
 
 on:
   push:
-    branches:
-    - '*'
-    tags:
-    - '*'
   pull_request:
 
 jobs:
   tests:
-    name: ${{ matrix.name }}
-    runs-on: ${{ matrix.os }}
-    strategy:
-      fail-fast: false
-      matrix:
-        include:
-          - name: Python 3.6
-            os: ubuntu-20.04
-            python: '3.6'
-          - name: Python 3.7
-            os: ubuntu-20.04
-            python: '3.7'
-          - name: Python 3.8
-            os: ubuntu-20.04
-            python: '3.8'
-          - name: Python 3.9
-            os: ubuntu-20.04
-            python: '3.9'
-          - name: Python 3.10
-            os: ubuntu-20.04
-            python: '3.10'
-    steps:
-    - name: Checkout code
-      uses: actions/checkout@v2
-      with:
-        submodules: 'true'
-        fetch-depth: 0
-    - name: Set up Python
-      uses: actions/setup-python@v2
-      with:
-        python-version: ${{ matrix.python }}
-    - name: Install HDF5 and MPI
-      if: startsWith(matrix.os, 'ubuntu')
-      run: sudo apt-get install libhdf5-serial-dev libmpich-dev
-    - name: Install tox
-      run: pip install tox
-    - name: Run tests
-      run: tox -e test-bitlevel
+    uses: OpenAstronomy/github-actions-workflows/.github/workflows/tox.yml@v1
+    with:
+      libraries: |
+        apt:
+          - libhdf5-serial-dev
+          - libmpich-dev
+      envs: |
+        - linux: py37-test-bitlevel
+          runs-on: ubuntu-20.04
+        - linux: py38-test-bitlevel
+          runs-on: ubuntu-20.04
+        - linux: py39-test-bitlevel
+          runs-on: ubuntu-20.04
+        - linux: py310-test-bitlevel
+          runs-on: ubuntu-20.04

.gitignore

@@ -1,3 +1,4 @@
+hyperion/_version.py
 hyperion/data/*
 build
 docs/_build
@@ -15,4 +16,5 @@ build_cmake
 .vscode
 dist
 Hyperion.egg-info
-
+*.so
+pip-wheel-metadata

docs/tutorials/tutorial_quantities_yt.rst

@@ -26,7 +26,7 @@ where ``pf`` is a ``StaticOutput`` yt object! This can then be used as a
 normal dataset in yt. For example, we can easily make projections of density
 and temperature along the y-axis::
 
-    from yt.mods import ProjectionPlot
+    from yt import ProjectionPlot
 
     prj = ProjectionPlot(pf, 'y', ['density', 'temperature'], 
                          center=[0.0, 0.0, 0.0])

hyperion/densities/ulrich_envelope.py

@@ -20,10 +20,10 @@ def delta_neg(r, q):
     rho = np.sqrt(-q.real ** 3)
     theta = np.arccos(r.real / rho)
 
-    s = (rho ** (1. / 3.) * np.cos(theta / 3.)).astype(np.complex)
+    s = (rho ** (1. / 3.) * np.cos(theta / 3.)).astype(complex)
     s.imag = rho ** (1. / 3.) * np.sin(theta / 3.)
 
-    t = (rho ** (1. / 3.) * np.cos(-theta / 3.)).astype(np.complex)
+    t = (rho ** (1. / 3.) * np.cos(-theta / 3.)).astype(complex)
     t.imag = rho ** (1. / 3.) * np.sin(-theta / 3.)
 
     return s, t
@@ -49,8 +49,8 @@ def cubic(c, d):
     Solve x**3 + c * x + d = 0
     '''
 
-    c = c.astype(np.complex)
-    d = d.astype(np.complex)
+    c = c.astype(complex)
+    d = d.astype(complex)
 
     q = c / 3.
     r = - d / 2.
@@ -59,8 +59,8 @@ def cubic(c, d):
 
     pos = delta >= 0.
 
-    s = np.zeros(c.shape, dtype=np.complex)
-    t = np.zeros(c.shape, dtype=np.complex)
+    s = np.zeros(c.shape, dtype=complex)
+    t = np.zeros(c.shape, dtype=complex)
 
     if np.sum(pos) > 0:
         s[pos], t[pos] = delta_pos(r[pos], delta[pos])
@@ -69,8 +69,8 @@ def cubic(c, d):
         s[~pos], t[~pos] = delta_neg(r[~pos], q[~pos])
 
     x1 = s + t
-    x2 = - (s + t) / 2. + np.sqrt(3.) / 2. * (s - t) * np.complex(0., 1.)
-    x3 = - (s + t) / 2. - np.sqrt(3.) / 2. * (s - t) * np.complex(0., 1.)
+    x2 = - (s + t) / 2. + np.sqrt(3.) / 2. * (s - t) * complex(0., 1.)
+    x3 = - (s + t) / 2. - np.sqrt(3.) / 2. * (s - t) * complex(0., 1.)
 
     return x1, x2, x3
 

hyperion/dust/emissivities.py

@@ -151,9 +151,9 @@ def hash(self):
         h = hashlib.md5()
         h.update(str(self.is_lte).encode('utf-8'))
         h.update(self.var_name.encode('utf-8'))
-        h.update(self.var.tostring())
-        h.update(self.nu.tostring())
-        h.update(self.jnu.tostring())
+        h.update(self.var.tobytes())
+        h.update(self.nu.tobytes())
+        h.update(self.jnu.tobytes())
         return h.hexdigest()
 
     def __setattr__(self, attribute, value):

hyperion/dust/mean_opacities.py

@@ -171,12 +171,12 @@ def plot(self, figure, subplot):
 
     def hash(self):
         h = hashlib.md5()
-        h.update(self.temperature.tostring())
-        h.update(self.specific_energy.tostring())
-        h.update(self.chi_planck.tostring())
-        h.update(self.kappa_planck.tostring())
-        h.update(self.chi_inv_planck.tostring())
-        h.update(self.kappa_inv_planck.tostring())
-        h.update(self.chi_rosseland.tostring())
-        h.update(self.kappa_rosseland.tostring())
+        h.update(self.temperature.tobytes())
+        h.update(self.specific_energy.tobytes())
+        h.update(self.chi_planck.tobytes())
+        h.update(self.kappa_planck.tobytes())
+        h.update(self.chi_inv_planck.tobytes())
+        h.update(self.kappa_inv_planck.tobytes())
+        h.update(self.chi_rosseland.tobytes())
+        h.update(self.kappa_rosseland.tobytes())
         return h.hexdigest()

hyperion/dust/optical_properties.py

@@ -383,14 +383,14 @@ def plot(self, figure, subplots):
 
     def hash(self):
         h = hashlib.md5()
-        h.update(self.nu.tostring())
-        h.update(self.chi.tostring())
-        h.update(self.albedo.tostring())
-        h.update(self.mu.tostring())
-        h.update(self.P1.tostring())
-        h.update(self.P2.tostring())
-        h.update(self.P3.tostring())
-        h.update(self.P4.tostring())
+        h.update(self.nu.tobytes())
+        h.update(self.chi.tobytes())
+        h.update(self.albedo.tobytes())
+        h.update(self.mu.tobytes())
+        h.update(self.P1.tobytes())
+        h.update(self.P2.tobytes())
+        h.update(self.P3.tobytes())
+        h.update(self.P4.tobytes())
         return h.hexdigest()
 
     def __setattr__(self, attribute, value):

hyperion/grid/amr_grid.py

@@ -602,7 +602,7 @@ def from_yt(cls, ds, quantity_mapping={}):
             >>> ds = load('DD0010/moving7_0010')
             >>> def _dust_density(field, data):
             ...     return data[('gas', 'density')].in_units('g/cm**3') * 0.01
-            >>> ds.add_field(('gas', 'dust_density'), function=_dust_density, units='g/cm**3')
+            >>> ds.add_field(('gas', 'dust_density'), function=_dust_density, units='g/cm**3', sampling_type='cell')
 
             >>> amr = AMRGrid.from_yt(ds, quantity_mapping={'density':('gas', 'dust_density')})
         """

hyperion/grid/cartesian_grid.py

@@ -392,9 +392,9 @@ def write_single_array(self, group, name, array, copy=True, absolute_paths=False
 
     def get_geometry_id(self):
         geo_hash = hashlib.md5()
-        geo_hash.update(self.x_wall.tostring())
-        geo_hash.update(self.y_wall.tostring())
-        geo_hash.update(self.z_wall.tostring())
+        geo_hash.update(self.x_wall.tobytes())
+        geo_hash.update(self.y_wall.tobytes())
+        geo_hash.update(self.z_wall.tobytes())
         return geo_hash.hexdigest()
 
     def __getitem__(self, item):

hyperion/grid/cylindrical_polar_grid.py

@@ -420,9 +420,9 @@ def write_single_array(self, group, name, array, copy=True, absolute_paths=False
 
     def get_geometry_id(self):
         geo_hash = hashlib.md5()
-        geo_hash.update(self.w_wall.tostring())
-        geo_hash.update(self.z_wall.tostring())
-        geo_hash.update(self.p_wall.tostring())
+        geo_hash.update(self.w_wall.tobytes())
+        geo_hash.update(self.z_wall.tobytes())
+        geo_hash.update(self.p_wall.tobytes())
         return geo_hash.hexdigest()
 
     def __getitem__(self, item):

hyperion/grid/octree_grid.py

@@ -196,7 +196,7 @@ def refined(self, value):
 
     def _validate(self, value):
 
-        value_hash = hashlib.md5(value.tostring()).hexdigest()
+        value_hash = hashlib.md5(value.tobytes()).hexdigest()
 
         if value_hash in self._validate_cache:
             return value
@@ -205,7 +205,7 @@ def _validate(self, value):
 
         # Check that refined array reduces to a single False if removing all
         # levels of refinement.
-        refined_str = value.tostring()
+        refined_str = value.tobytes()
         previous = ''
         while True:
             refined_str = refined_str.replace(b'\x01\x00\x00\x00\x00\x00\x00\x00\x00', b'\x00')
@@ -491,7 +491,7 @@ def get_geometry_id(self):
         geo_hash.update(struct.pack('>d', self.dx))
         geo_hash.update(struct.pack('>d', self.dy))
         geo_hash.update(struct.pack('>d', self.dz))
-        geo_hash.update(self.refined.tostring())
+        geo_hash.update(self.refined.tobytes())
         return geo_hash.hexdigest()
 
     def __getitem__(self, item):

hyperion/grid/spherical_polar_grid.py

@@ -430,9 +430,9 @@ def write_single_array(self, group, name, array, copy=True, absolute_paths=False
 
     def get_geometry_id(self):
         geo_hash = hashlib.md5()
-        geo_hash.update(self.r_wall.tostring())
-        geo_hash.update(self.t_wall.tostring())
-        geo_hash.update(self.p_wall.tostring())
+        geo_hash.update(self.r_wall.tobytes())
+        geo_hash.update(self.t_wall.tobytes())
+        geo_hash.update(self.p_wall.tobytes())
         return geo_hash.hexdigest()
 
     def __getitem__(self, item):

hyperion/grid/tests/test_yt.py

@@ -75,7 +75,7 @@ def setup_method(self, method):
     @pytest.mark.parametrize(('grid_type'), ALL_GRID_TYPES)
     def test_to_yt(self, tmpdir, grid_type):
 
-        from yt.mods import ProjectionPlot
+        from yt import ProjectionPlot
 
         g = self.grid[grid_type]
         g['density'] = []
@@ -101,7 +101,7 @@ def test_from_yt(tmpdir):
     def _dust_density(field, data):
         return data["density"].in_units('g/cm**3') * 0.01
 
-    ds.add_field(("gas", "dust_density"), function=_dust_density, units='g/cm**3')
+    ds.add_field(("gas", "dust_density"), function=_dust_density, units='g/cm**3', sampling_type='cell')
 
     amr = AMRGrid.from_yt(ds, quantity_mapping={'density': ('gas', 'dust_density')})
 
@@ -147,7 +147,7 @@ def test_axis_ordering_cartesian():
     g['density'] = []
     g['density'].append(density)
 
-    from yt.mods import ProjectionPlot, SlicePlot
+    from yt import ProjectionPlot, SlicePlot
 
     pf = g.to_yt()
 
@@ -177,7 +177,7 @@ def test_axis_ordering_amr():
     grid.quantities['density'] = []
     grid.quantities['density'].append(np.arange(grid.nz)[:, None, None] * np.ones((grid.nz, grid.ny, grid.nx)))
 
-    from yt.mods import ProjectionPlot, SlicePlot
+    from yt import ProjectionPlot, SlicePlot
 
     pf = g.to_yt()
 

hyperion/grid/voronoi_grid.py

@@ -527,9 +527,9 @@ def write_single_array(self, group, name, array, copy=True, absolute_paths=False
     def get_geometry_id(self):
         # The grid is uniquely defined by the points and the bounds
         geo_hash = hashlib.md5()
-        geo_hash.update(self.x.tostring())
-        geo_hash.update(self.y.tostring())
-        geo_hash.update(self.z.tostring())
+        geo_hash.update(self.x.tobytes())
+        geo_hash.update(self.y.tobytes())
+        geo_hash.update(self.z.tobytes())
         geo_hash.update(struct.pack('>d', self.xmin))
         geo_hash.update(struct.pack('>d', self.xmax))
         geo_hash.update(struct.pack('>d', self.ymin))

hyperion/grid/yt3_wrappers.py

@@ -107,7 +107,7 @@ def amr_grid_to_yt_stream(levels, dust_id=0):
 
     bbox = np.array([[xmin, xmax], [ymin, ymax], [zmin, zmax]])
 
-    from yt.mods import load_amr_grids
+    from yt import load_amr_grids
 
     spf = load_amr_grids(grid_data, domain_dimensions, bbox=bbox,
                          geometry=('cartesian', ('x', 'y', 'z')))
@@ -154,7 +154,7 @@ def octree_grid_to_yt_stream(grid, dust_id=0):
     zmin = grid.z - grid.dz
     zmax = grid.z + grid.dz
 
-    from yt.mods import load_octree
+    from yt import load_octree
 
     quantities = {}
     for field in grid.quantities:
@@ -183,7 +183,7 @@ def cartesian_grid_to_yt_stream(grid, xmin, xmax, ymin, ymax, zmin, zmax, dust_i
         data[field] = grid.quantities[field][dust_id].transpose(), ''
 
     # Load cartesian grid into yt
-    from yt.mods import load_uniform_grid
+    from yt import load_uniform_grid
     spf = load_uniform_grid(data=data,
                             domain_dimensions=np.array(grid.shape[::-1], dtype=np.int32),
                             bbox=np.array([(xmin, xmax), (ymin, ymax), (zmin, zmax)]),
@@ -240,7 +240,7 @@ def yt_dataset_to_amr_grid(ds, quantity_mapping={}):
         >>> ds = load('DD0010/moving7_0010')
         >>> def _dust_density(field, data):
         ...     return data[('gas', 'density')].in_units('g/cm**3') * 0.01
-        >>> ds.add_field(('gas', 'dust_density'), function=_dust_density, units='g/cm**3')
+        >>> ds.add_field(('gas', 'dust_density'), function=_dust_density, units='g/cm**3', sampling_type='cell')
 
         >>> amr = yt_dataset_to_amr_grid(ds, quantity_mapping={'density':('gas', 'dust_density')})
     """

hyperion/model/tests/test_amr_checks.py

@@ -224,7 +224,7 @@ def test_shadowing_regression(tmpdir):
     m.write(tmpdir.join(random_id()).strpath)
     mo = m.run(tmpdir.join(random_id()).strpath)
 
-    from yt.mods import SlicePlot
+    from yt import SlicePlot
 
     g = mo.get_quantities()
 

hyperion/util/interpolate.py

@@ -58,7 +58,7 @@ def interp1d_fast(x, y, xval):
     if x.dtype != float or y.dtype != float:
         x, y = x.astype(float), y.astype(float)
     if np.isscalar(xval):
-        return interp1d_linear_scalar(x, y, np.float(xval))
+        return interp1d_linear_scalar(x, y, float(xval))
     else:
         if xval.ndim > 1:
             return interp1d_linear_array(x, y, xval.flatten()).reshape(xval.shape)
@@ -74,7 +74,7 @@ def interp1d_fast_loglog(x, y, xval):
     if x.dtype != float or y.dtype != float:
         x, y = x.astype(float), y.astype(float)
     if np.isscalar(xval):
-        return interp1d_loglog_scalar(x, y, np.float(xval))
+        return interp1d_loglog_scalar(x, y, float(xval))
     else:
         if xval.ndim > 1:
             return interp1d_loglog_array(x, y, xval.flatten()).reshape(xval.shape)
@@ -90,7 +90,7 @@ def interp1d_fast_linlog(x, y, xval):
     if x.dtype != float or y.dtype != float:
         x, y = x.astype(float), y.astype(float)
     if np.isscalar(xval):
-        return interp1d_linlog_scalar(x, y, np.float(xval))
+        return interp1d_linlog_scalar(x, y, float(xval))
     else:
         if xval.ndim > 1:
             return interp1d_linlog_array(x, y, xval.flatten()).reshape(xval.shape)
@@ -106,7 +106,7 @@ def interp1d_fast_loglin(x, y, xval):
     if x.dtype != float or y.dtype != float:
         x, y = x.astype(float), y.astype(float)
     if np.isscalar(xval):
-        return interp1d_loglin_scalar(x, y, np.float(xval))
+        return interp1d_loglin_scalar(x, y, float(xval))
     else:
         if xval.ndim > 1:
             return interp1d_loglin_array(x, y, xval.flatten()).reshape(xval.shape)