Ensure direction vector n is always a unit vector

sfstoolbox · Dec 21, 2016 · 8a97603 · 8a97603
1 parent 77f1349
commit 8a97603
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Showing 3 changed files with 13 additions and 11 deletions.
diff --git a/sfs/mono/drivingfunction.py b/sfs/mono/drivingfunction.py
@@ -86,7 +86,7 @@ def _wfs_plane(omega, x0, n0, n=[0, 1, 0], c=None):
  """
  x0 = util.asarray_of_rows(x0)
  n0 = util.asarray_of_rows(n0)
- n = util.asarray_1d(n)
+ n = util.normalize_vector(n)
  k = util.wavenumber(omega, c)
  return 2j * k * np.inner(n, n0) * np.exp(-1j * k * np.inner(n, x0))
 
@@ -106,7 +106,7 @@ def wfs_25d_plane(omega, x0, n0, n=[0, 1, 0], xref=[0, 0, 0], c=None,
  """
  x0 = util.asarray_of_rows(x0)
  n0 = util.asarray_of_rows(n0)
- n = util.asarray_1d(n)
+ n = util.normalize_vector(n)
  xref = util.asarray_1d(xref)
  k = util.wavenumber(omega, c)
  return wfs_25d_preeq(omega, omalias, c) * \
@@ -179,7 +179,7 @@ def wfs_25d_preeq(omega, omalias, c):
 def delay_3d_plane(omega, x0, n0, n=[0, 1, 0], c=None):
  """Plane wave by simple delay of secondary sources."""
  x0 = util.asarray_of_rows(x0)
- n = util.asarray_1d(n)
+ n = util.normalize_vector(n)
  k = util.wavenumber(omega, c)
  return np.exp(-1j * k * np.inner(n, x0))
 
@@ -191,7 +191,7 @@ def source_selection_plane(n0, n):
 
  """
  n0 = util.asarray_of_rows(n0)
- n = util.asarray_1d(n)
+ n = util.normalize_vector(n)
  return np.inner(n, n0) >= defs.selection_tolerance
 
 
@@ -225,7 +225,7 @@ def source_selection_focused(ns, x0, xs):
  """
  x0 = util.asarray_of_rows(x0)
  xs = util.asarray_1d(xs)
- ns = util.asarray_1d(ns)
+ ns = util.normalize_vector(ns)
  ds = xs - x0
  return inner1d(ns, ds) >= defs.selection_tolerance
 
@@ -251,7 +251,7 @@ def nfchoa_2d_plane(omega, x0, r0, n=[0, 1, 0], max_order=None, c=None):
  """
  x0 = util.asarray_of_rows(x0)
  k = util.wavenumber(omega, c)
- n = util.asarray_1d(n)
+ n = util.normalize_vector(n)
  phi, _, r = util.cart2sph(*n)
  phi0 = util.cart2sph(*x0.T)[0]
  M = _max_order_circular_harmonics(len(x0), max_order)
@@ -305,7 +305,7 @@ def nfchoa_25d_plane(omega, x0, r0, n=[0, 1, 0], max_order=None, c=None):
  """
  x0 = util.asarray_of_rows(x0)
  k = util.wavenumber(omega, c)
- n = util.asarray_1d(n)
+ n = util.normalize_vector(n)
  phi, _, r = util.cart2sph(*n)
  phi0 = util.cart2sph(*x0.T)[0]
  M = _max_order_circular_harmonics(len(x0), max_order)
@@ -345,7 +345,7 @@ def sdm_2d_plane(omega, x0, n0, n=[0, 1, 0], c=None):
  """
  x0 = util.asarray_of_rows(x0)
  n0 = util.asarray_of_rows(n0)
- n = util.asarray_1d(n)
+ n = util.normalize_vector(n)
  k = util.wavenumber(omega, c)
  return k * n[1] * np.exp(-1j * k * n[0] * x0[:, 0])
 
@@ -361,7 +361,7 @@ def sdm_25d_plane(omega, x0, n0, n=[0, 1, 0], xref=[0, 0, 0], c=None):
  """
  x0 = util.asarray_of_rows(x0)
  n0 = util.asarray_of_rows(n0)
- n = util.asarray_1d(n)
+ n = util.normalize_vector(n)
  xref = util.asarray_1d(xref)
  k = util.wavenumber(omega, c)
  return 4j * np.exp(-1j*k*n[1]*xref[1]) / hankel2(0, k*n[1]*xref[1]) * \
@@ -420,6 +420,7 @@ def esa_edge_2d_plane(omega, x0, n=[0, 1, 0], alpha=3/2*np.pi, Nc=None, c=None):
 
  """
  x0 = np.asarray(x0)
+ n = util.normalize_vector(n)
  k = util.wavenumber(omega, c)
  phi_s = np.arctan2(n[1], n[0]) + np.pi
  L = x0.shape[0]
@@ -477,6 +478,7 @@ def esa_edge_dipole_2d_plane(omega, x0, n=[0, 1, 0], alpha=3/2*np.pi, Nc=None, c
 
  """
  x0 = np.asarray(x0)
+ n = util.normalize_vector(n)
  k = util.wavenumber(omega, c)
  phi_s = np.arctan2(n[1], n[0]) + np.pi
  L = x0.shape[0]

diff --git a/sfs/mono/source.py b/sfs/mono/source.py
@@ -489,7 +489,7 @@ def plane(omega, x0, n0, grid, c=None):
  """
  k = util.wavenumber(omega, c)
  x0 = util.asarray_1d(x0)
- n0 = util.asarray_1d(n0)
+ n0 = util.normalize_vector(n0)
  grid = util.as_xyz_components(grid)
  return np.exp(-1j * k * np.inner(grid - x0, n0))
 

diff --git a/sfs/time/drivingfunction.py b/sfs/time/drivingfunction.py
@@ -60,7 +60,7 @@ def wfs_25d_plane(x0, n0, n=[0, 1, 0], xref=[0, 0, 0], c=None):
  c = defs.c
  x0 = util.asarray_of_rows(x0)
  n0 = util.asarray_of_rows(n0)
- n = util.asarray_1d(n)
+ n = util.normalize_vector(n)
  xref = util.asarray_1d(xref)
  g0 = np.sqrt(2 * np.pi * np.linalg.norm(xref - x0, axis=1))
  delays = inner1d(n, x0) / c