Keyword-only arguments everywhere

doc/examples/horizontal_plane_arrays.py

@@ -29,12 +29,12 @@ def compute_and_plot_soundfield(title):
     """Compute and plot synthesized sound field."""
     print('Computing', title)
 
-    twin = tapering(selection, talpha)
+    twin = tapering(selection, alpha=talpha)
     p = sfs.fd.synthesize(d, twin, array, secondary_source, grid=grid)
 
     plt.figure(figsize=(15, 15))
     plt.cla()
-    sfs.plot2d.amplitude(p, grid, xnorm)
+    sfs.plot2d.amplitude(p, grid, xnorm=xnorm)
     sfs.plot2d.loudspeakers(array.x, array.n, twin)
     sfs.plot2d.virtualsource(xs)
     sfs.plot2d.virtualsource([0, 0], npw, type='plane')

doc/examples/mirror-image-source-model.ipynb

@@ -94,7 +94,7 @@
    "source": [
     "grid = sfs.util.xyz_grid([0, L[0]], [0, L[1]], 1.5, spacing=0.02)\n",
     "P = sfs.fd.source.point_image_sources(omega, x0, grid, L,\n",
-    "                                      max_order, coeffs=coeffs)"
+    "                                      max_order=max_order, coeffs=coeffs)"
    ]
   },
   {

doc/examples/sound_field_synthesis.py

@@ -49,7 +49,7 @@
 #d, selection, secondary_source = sfs.fd.wfs.line_2d(omega, array.x, array.n, xs)
 
 #d, selection, secondary_source = sfs.fd.wfs.plane_2d(omega, array.x, array.n, npw)
-d, selection, secondary_source = sfs.fd.wfs.plane_25d(omega, array.x, array.n, npw, xref)
+d, selection, secondary_source = sfs.fd.wfs.plane_25d(omega, array.x, array.n, npw, xref=xref)
 #d, selection, secondary_source = sfs.fd.wfs.plane_3d(omega, array.x, array.n, npw)
 
 #d, selection, secondary_source = sfs.fd.wfs.point_2d(omega, array.x, array.n, xs)
@@ -64,16 +64,16 @@
 
 # === compute tapering window ===
 #twin = sfs.tapering.none(selection)
-#twin = sfs.tapering.kaiser(selection, 8.6)
-twin = sfs.tapering.tukey(selection, 0.3)
+#twin = sfs.tapering.kaiser(selection, beta=8.6)
+twin = sfs.tapering.tukey(selection, alpha=0.3)
 
 # === compute synthesized sound field ===
 p = sfs.fd.synthesize(d, twin, array, secondary_source, grid=grid)
 
 
 # === plot synthesized sound field ===
 plt.figure(figsize=(10, 10))
-sfs.plot2d.amplitude(p, grid, [0, 0, 0])
+sfs.plot2d.amplitude(p, grid, xnorm=[0, 0, 0])
 sfs.plot2d.loudspeakers(array.x, array.n, twin)
 plt.grid()
 plt.savefig('soundfield.png')

doc/examples/time_domain.py

@@ -29,7 +29,7 @@
 d = sfs.td.wfs.driving_signals(d_delay, d_weight, signal)
 
 # test soundfield
-twin = sfs.tapering.tukey(selection, .3)
+twin = sfs.tapering.tukey(selection, alpha=0.3)
 
 p = sfs.td.synthesize(d, twin, array,
                       secondary_source, observation_time=t, grid=grid)
@@ -54,7 +54,7 @@
 d = sfs.td.wfs.driving_signals(d_delay, d_weight, signal)
 
 # test soundfield
-twin = sfs.tapering.tukey(selection, .3)
+twin = sfs.tapering.tukey(selection, alpha=0.3)
 p = sfs.td.synthesize(d, twin, array,
                       secondary_source, observation_time=t, grid=grid)
 
@@ -76,7 +76,7 @@
 d = sfs.td.wfs.driving_signals(d_delay, d_weight, signal)
 
 # test soundfield
-twin = sfs.tapering.tukey(selection, .3)
+twin = sfs.tapering.tukey(selection, alpha=0.3)
 p = sfs.td.synthesize(d, twin, array,
                       secondary_source, observation_time=t, grid=grid)
 p = p * 100  # scale absolute amplitude

sfs/array.py

@@ -84,7 +84,7 @@ def as_secondary_source_distribution(arg, **kwargs):
     return SecondarySourceDistribution(x, n, a)
 
 
-def linear(N, spacing, center=[0, 0, 0], orientation=[1, 0, 0]):
+def linear(N, spacing, *, center=[0, 0, 0], orientation=[1, 0, 0]):
     """Return linear, equidistantly sampled secondary source distribution.
 
     Parameters
@@ -119,7 +119,7 @@ def linear(N, spacing, center=[0, 0, 0], orientation=[1, 0, 0]):
     return _linear_helper(np.arange(N) * spacing, center, orientation)
 
 
-def linear_diff(distances, center=[0, 0, 0], orientation=[1, 0, 0]):
+def linear_diff(distances, *, center=[0, 0, 0], orientation=[1, 0, 0]):
     """Return linear secondary source distribution from a list of distances.
 
     Parameters
@@ -152,7 +152,7 @@ def linear_diff(distances, center=[0, 0, 0], orientation=[1, 0, 0]):
     return _linear_helper(ycoordinates, center, orientation)
 
 
-def linear_random(N, min_spacing, max_spacing, center=[0, 0, 0],
+def linear_random(N, min_spacing, max_spacing, *, center=[0, 0, 0],
                   orientation=[1, 0, 0], seed=None):
     """Return randomly sampled linear array.
 
@@ -190,10 +190,10 @@ def linear_random(N, min_spacing, max_spacing, center=[0, 0, 0],
     """
     r = np.random.RandomState(seed)
     distances = r.uniform(min_spacing, max_spacing, size=N-1)
-    return linear_diff(distances, center, orientation)
+    return linear_diff(distances, center=center, orientation=orientation)
 
 
-def circular(N, R, center=[0, 0, 0]):
+def circular(N, R, *, center=[0, 0, 0]):
     """Return circular secondary source distribution parallel to the xy-plane.
 
     Parameters
@@ -235,7 +235,7 @@ def circular(N, R, center=[0, 0, 0]):
     return SecondarySourceDistribution(positions, normals, weights)
 
 
-def rectangular(N, spacing, center=[0, 0, 0], orientation=[1, 0, 0]):
+def rectangular(N, spacing, *, center=[0, 0, 0], orientation=[1, 0, 0]):
     """Return rectangular secondary source distribution.
 
     Parameters
@@ -272,18 +272,22 @@ def rectangular(N, spacing, center=[0, 0, 0], orientation=[1, 0, 0]):
     offset1 = spacing * (N2 - 1) / 2 + spacing / np.sqrt(2)
     offset2 = spacing * (N1 - 1) / 2 + spacing / np.sqrt(2)
     positions, normals, weights = concatenate(
-        linear(N1, spacing, [-offset1, 0, 0], [1, 0, 0]),  # left
-        linear(N2, spacing, [0, offset2, 0], [0, -1, 0]),  # upper
-        linear(N1, spacing, [offset1, 0, 0], [-1, 0, 0]),  # right
-        linear(N2, spacing, [0, -offset2, 0], [0, 1, 0]),  # lower
+        # left
+        linear(N1, spacing, center=[-offset1, 0, 0], orientation=[1, 0, 0]),
+        # upper
+        linear(N2, spacing, center=[0, offset2, 0], orientation=[0, -1, 0]),
+        # right
+        linear(N1, spacing, center=[offset1, 0, 0], orientation=[-1, 0, 0]),
+        # lower
+        linear(N2, spacing, center=[0, -offset2, 0], orientation=[0, 1, 0]),
     )
     positions, normals = _rotate_array(positions, normals,
                                        [1, 0, 0], orientation)
     positions += center
     return SecondarySourceDistribution(positions, normals, weights)
 
 
-def rounded_edge(Nxy, Nr, dx, center=[0, 0, 0], orientation=[1, 0, 0]):
+def rounded_edge(Nxy, Nr, dx, *, center=[0, 0, 0], orientation=[1, 0, 0]):
     """Return SSD along the xy-axis with rounded edge at the origin.
 
     Parameters
@@ -357,7 +361,7 @@ def rounded_edge(Nxy, Nr, dx, center=[0, 0, 0], orientation=[1, 0, 0]):
     return SecondarySourceDistribution(positions, directions, weights)
 
 
-def edge(Nxy, dx, center=[0, 0, 0], orientation=[1, 0, 0]):
+def edge(Nxy, dx, *, center=[0, 0, 0], orientation=[1, 0, 0]):
     """Return SSD along the xy-axis with sharp edge at the origin.
 
     Parameters
@@ -409,7 +413,7 @@ def edge(Nxy, dx, center=[0, 0, 0], orientation=[1, 0, 0]):
     return SecondarySourceDistribution(positions, directions, weights)
 
 
-def planar(N, spacing, center=[0, 0, 0], orientation=[1, 0, 0]):
+def planar(N, spacing, *, center=[0, 0, 0], orientation=[1, 0, 0]):
     """Return planar secondary source distribtion.
 
     Parameters
@@ -460,7 +464,7 @@ def planar(N, spacing, center=[0, 0, 0], orientation=[1, 0, 0]):
     return SecondarySourceDistribution(positions, normals, weights)
 
 
-def cube(N, spacing, center=[0, 0, 0], orientation=[1, 0, 0]):
+def cube(N, spacing, *, center=[0, 0, 0], orientation=[1, 0, 0]):
     """Return cube-shaped secondary source distribtion.
 
     Parameters
@@ -496,24 +500,31 @@ def cube(N, spacing, center=[0, 0, 0], orientation=[1, 0, 0]):
 
     """
     N1, N2, N3 = (N, N, N) if np.isscalar(N) else N
-    offset1 = spacing * (N2 - 1) / 2 + spacing / np.sqrt(2)
-    offset2 = spacing * (N1 - 1) / 2 + spacing / np.sqrt(2)
-    offset3 = spacing * (N3 - 1) / 2 + spacing / np.sqrt(2)
+    d = spacing
+    offset1 = d * (N2 - 1) / 2 + d / np.sqrt(2)
+    offset2 = d * (N1 - 1) / 2 + d / np.sqrt(2)
+    offset3 = d * (N3 - 1) / 2 + d / np.sqrt(2)
     positions, directions, weights = concatenate(
-        planar((N1, N3), spacing, [-offset1, 0, 0], [1, 0, 0]),  # west
-        planar((N2, N3), spacing, [0, offset2, 0], [0, -1, 0]),  # north
-        planar((N1, N3), spacing, [offset1, 0, 0], [-1, 0, 0]),  # east
-        planar((N2, N3), spacing, [0, -offset2, 0], [0, 1, 0]),  # south
-        planar((N2, N1), spacing, [0, 0, -offset3], [0, 0, 1]),  # bottom
-        planar((N2, N1), spacing, [0, 0, offset3], [0, 0, -1]),  # top
+        # west
+        planar((N1, N3), d, center=[-offset1, 0, 0], orientation=[1, 0, 0]),
+        # north
+        planar((N2, N3), d, center=[0, offset2, 0], orientation=[0, -1, 0]),
+        # east
+        planar((N1, N3), d, center=[offset1, 0, 0], orientation=[-1, 0, 0]),
+        # south
+        planar((N2, N3), d, center=[0, -offset2, 0], orientation=[0, 1, 0]),
+        # bottom
+        planar((N2, N1), d, center=[0, 0, -offset3], orientation=[0, 0, 1]),
+        # top
+        planar((N2, N1), d, center=[0, 0, offset3], orientation=[0, 0, -1]),
     )
     positions, directions = _rotate_array(positions, directions,
                                           [1, 0, 0], orientation)
     positions += center
     return SecondarySourceDistribution(positions, directions, weights)
 
 
-def sphere_load(file, radius, center=[0, 0, 0]):
+def sphere_load(file, radius, *, center=[0, 0, 0]):
     """Load spherical secondary source distribution from file.
 
     ASCII Format (see MATLAB SFS Toolbox) with 4 numbers (3 for the cartesian
@@ -562,7 +573,7 @@ def sphere_load(file, radius, center=[0, 0, 0]):
     return SecondarySourceDistribution(positions, normals, weights)
 
 
-def load(file, center=[0, 0, 0], orientation=[1, 0, 0]):
+def load(file, *, center=[0, 0, 0], orientation=[1, 0, 0]):
     """Load secondary source distribution from file.
 
     Comma Separated Values (CSV) format with 7 values
@@ -615,7 +626,7 @@ def load(file, center=[0, 0, 0], orientation=[1, 0, 0]):
     return SecondarySourceDistribution(positions, normals, weights)
 
 
-def weights_midpoint(positions, closed):
+def weights_midpoint(positions, *, closed):
     """Calculate loudspeaker weights for a simply connected array.
 
     The weights are calculated according to the midpoint rule.

sfs/fd/__init__.py

@@ -63,7 +63,7 @@ def secondary_source_point(omega, c):
     """Create a point source for use in `sfs.fd.synthesize()`."""
 
     def secondary_source(position, _, grid):
-        return source.point(omega, position, grid, c)
+        return source.point(omega, position, grid, c=c)
 
     return secondary_source
 
@@ -72,7 +72,7 @@ def secondary_source_line(omega, c):
     """Create a line source for use in `sfs.fd.synthesize()`."""
 
     def secondary_source(position, _, grid):
-        return source.line(omega, position, grid, c)
+        return source.line(omega, position, grid, c=c)
 
     return secondary_source
 

sfs/fd/esa.py

@@ -16,8 +16,7 @@
 from . import secondary_source_line, secondary_source_point
 
 
-def plane_2d_edge(omega, x0, n=[0, 1, 0], alpha=3/2*np.pi, Nc=None,
-             c=None):
+def plane_2d_edge(omega, x0, n=[0, 1, 0], *, alpha=3/2*np.pi, Nc=None, c=None):
     r"""Driving function for 2-dimensional plane wave with edge ESA.
 
     Driving function for a virtual plane wave using the 2-dimensional ESA
@@ -87,8 +86,8 @@ def plane_2d_edge(omega, x0, n=[0, 1, 0], alpha=3/2*np.pi, Nc=None,
     return 4*np.pi/alpha * d, selection, secondary_source_line(omega, c)
 
 
-def plane_2d_edge_dipole_ssd(omega, x0, n=[0, 1, 0], alpha=3/2*np.pi, Nc=None,
-                             c=None):
+def plane_2d_edge_dipole_ssd(omega, x0, n=[0, 1, 0], *, alpha=3/2*np.pi,
+                             Nc=None, c=None):
     r"""Driving function for 2-dimensional plane wave with edge dipole ESA.
 
     Driving function for a virtual plane wave using the 2-dimensional ESA
@@ -155,7 +154,7 @@ def plane_2d_edge_dipole_ssd(omega, x0, n=[0, 1, 0], alpha=3/2*np.pi, Nc=None,
     return 4*np.pi/alpha * d
 
 
-def line_2d_edge(omega, x0, xs, alpha=3/2*np.pi, Nc=None, c=None):
+def line_2d_edge(omega, x0, xs, *, alpha=3/2*np.pi, Nc=None, c=None):
     r"""Driving function for 2-dimensional line source with edge ESA.
 
     Driving function for a virtual line source using the 2-dimensional ESA
@@ -229,7 +228,8 @@ def line_2d_edge(omega, x0, xs, alpha=3/2*np.pi, Nc=None, c=None):
     return -1j*np.pi/alpha * d, selection, secondary_source_line(omega, c)
 
 
-def line_2d_edge_dipole_ssd(omega, x0, xs, alpha=3/2*np.pi, Nc=None, c=None):
+def line_2d_edge_dipole_ssd(omega, x0, xs, *, alpha=3/2*np.pi, Nc=None,
+                            c=None):
     r"""Driving function for 2-dimensional line source with edge dipole ESA.
 
     Driving function for a virtual line source using the 2-dimensional ESA
@@ -300,8 +300,8 @@ def line_2d_edge_dipole_ssd(omega, x0, xs, alpha=3/2*np.pi, Nc=None, c=None):
     return -1j*np.pi/alpha * d
 
 
-def point_25d_edge(omega, x0, xs, xref=[2, -2, 0], alpha=3/2*np.pi,
-              Nc=None, c=None):
+def point_25d_edge(omega, x0, xs, *, xref=[2, -2, 0], alpha=3/2*np.pi,
+                   Nc=None, c=None):
     r"""Driving function for 2.5-dimensional point source with edge ESA.
 
     Driving function for a virtual point source using the 2.5-dimensional

sfs/fd/nfchoa.py

@@ -35,7 +35,7 @@ def plot(d, selection, secondary_source):
 from . import secondary_source_point
 
 
-def plane_2d(omega, x0, r0, n=[0, 1, 0], max_order=None, c=None):
+def plane_2d(omega, x0, r0, n=[0, 1, 0], *, max_order=None, c=None):
     r"""Driving function for 2-dimensional NFC-HOA for a virtual plane wave.
 
     Parameters
@@ -101,7 +101,7 @@ def plane_2d(omega, x0, r0, n=[0, 1, 0], max_order=None, c=None):
     return -2j / (np.pi*r0) * d, selection, secondary_source_point(omega, c)
 
 
-def point_25d(omega, x0, r0, xs, max_order=None, c=None):
+def point_25d(omega, x0, r0, xs, *, max_order=None, c=None):
     r"""Driving function for 2.5-dimensional NFC-HOA for a virtual point source.
 
     Parameters
@@ -169,7 +169,7 @@ def point_25d(omega, x0, r0, xs, max_order=None, c=None):
     return d / (2 * np.pi * r0), selection, secondary_source_point(omega, c)
 
 
-def plane_25d(omega, x0, r0, n=[0, 1, 0], max_order=None, c=None):
+def plane_25d(omega, x0, r0, n=[0, 1, 0], *, max_order=None, c=None):
     r"""Driving function for 2.5-dimensional NFC-HOA for a virtual plane wave.
 
     Parameters

sfs/fd/sdm.py

@@ -34,7 +34,7 @@ def plot(d, selection, secondary_source):
 from . import secondary_source_line, secondary_source_point
 
 
-def line_2d(omega, x0, n0, xs, c=None):
+def line_2d(omega, x0, n0, xs, *, c=None):
     r"""Driving function for 2-dimensional SDM for a virtual line source.
 
     Parameters
@@ -87,7 +87,7 @@ def line_2d(omega, x0, n0, xs, c=None):
     return d, selection, secondary_source_line(omega, c)
 
 
-def plane_2d(omega, x0, n0, n=[0, 1, 0], c=None):
+def plane_2d(omega, x0, n0, n=[0, 1, 0], *, c=None):
     r"""Driving function for 2-dimensional SDM for a virtual plane wave.
 
     Parameters
@@ -142,7 +142,7 @@ def plane_2d(omega, x0, n0, n=[0, 1, 0], c=None):
     return d, selection, secondary_source_line(omega, c)
 
 
-def plane_25d(omega, x0, n0, n=[0, 1, 0], xref=[0, 0, 0], c=None):
+def plane_25d(omega, x0, n0, n=[0, 1, 0], *, xref=[0, 0, 0], c=None):
     r"""Driving function for 2.5-dimensional SDM for a virtual plane wave.
 
     Parameters
@@ -182,7 +182,7 @@ def plane_25d(omega, x0, n0, n=[0, 1, 0], xref=[0, 0, 0], c=None):
         :context: close-figs
 
         d, selection, secondary_source = sfs.fd.sdm.plane_25d(
-            omega, array.x, array.n, npw, [0, -1, 0])
+            omega, array.x, array.n, npw, xref=[0, -1, 0])
         plot(d, selection, secondary_source)
 
     """
@@ -197,7 +197,7 @@ def plane_25d(omega, x0, n0, n=[0, 1, 0], xref=[0, 0, 0], c=None):
     return d, selection, secondary_source_point(omega, c)
 
 
-def point_25d(omega, x0, n0, xs, xref=[0, 0, 0], c=None):
+def point_25d(omega, x0, n0, xs, *, xref=[0, 0, 0], c=None):
     r"""Driving function for 2.5-dimensional SDM for a virtual point source.
 
     Parameters
@@ -237,7 +237,7 @@ def point_25d(omega, x0, n0, xs, xref=[0, 0, 0], c=None):
         :context: close-figs
 
         d, selection, secondary_source = sfs.fd.sdm.point_25d(
-            omega, array.x, array.n, xs, [0, -1, 0])
+            omega, array.x, array.n, xs, xref=[0, -1, 0])
         plot(d, selection, secondary_source)
 
     """