address JDM review, switch from FFT to DFT

s2fft/precompute_transforms/custom_ops.py

@@ -17,11 +17,9 @@ def wigner_subset_to_s2(
     Transforms an arbitrary subset of Wigner coefficients onto a subset of spin signals
     on the sphere.
 
-        This function takes a collection of spin spherical harmonic coefficients each with
-        a different (though not necessarily unique) spin and maps them back to their
-        corresponding pixel-space representations. Following this operation one may
-        liftn this collection of spin signals to a signal on SO(3) by exploiting the
-        correct Mackey functions.
+    This function takes a collection of spin spherical harmonic coefficients each with
+    a different (though not necessarily unique) spin and maps them back to their
+    corresponding pixel-space representations.
 
     Args:
         flmn (np.ndarray): Collection of spin spherical harmonic coefficients
@@ -33,15 +31,25 @@ def wigner_subset_to_s2(
         sampling (str, optional): Sampling scheme.  Supported sampling schemes include
             {"mw", "mwss"}. Defaults to "mw".
 
+    Raises:
+        ValueError: If sampling scheme is not recognised.
+        ValueError: If the number of spins does not match the number of Wigner coefficients.
+
     Returns:
-        np.ndarray: A collection of spin signals with shape :math:`[batch, n_s, n_\theta, n_\phi, channels]`.
+        np.ndarray: A collection of spin signals with
+            shape :math:`[batch, n_s, n_\theta, n_\phi, channels]`.
 
     """
     if sampling.lower() not in ["mw", "mwss"]:
         raise ValueError(
             f"Fourier-Wigner algorithm does not support {sampling} sampling."
         )
 
+    if flmn.shape[1] != spins.shape[0]:
+        raise ValueError(
+            f"Number of spins specified {spins.shape[0]} does not match the number of Wigner coefficients {flmn.shape[1]}"
+        )
+
     # EXTRACT VARIOUS PRECOMPUTES
     Delta, _ = DW
 
@@ -93,9 +101,7 @@ def wigner_subset_to_s2_jax(
 
         This function takes a collection of spin spherical harmonic coefficients each with
         a different (though not necessarily unique) spin and maps them back to their
-        corresponding pixel-space representations. Following this operation one may
-        liftn this collection of spin signals to a signal on SO(3) by exploiting the
-        correct Mackey functions.
+        corresponding pixel-space representations.
 
     Args:
         flmn (jnp.ndarray): Collection of spin spherical harmonic coefficients
@@ -107,6 +113,10 @@ def wigner_subset_to_s2_jax(
         sampling (str, optional): Sampling scheme.  Supported sampling schemes include
             {"mw", "mwss"}. Defaults to "mw".
 
+    Raises:
+        ValueError: If sampling scheme is not recognised.
+        ValueError: If the number of spins does not match the number of Wigner coefficients.
+
     Returns:
         jnp.ndarray: A collection of spin signals with shape :math:`[batch, n_s, n_\theta, n_\phi, channels]`.
 
@@ -116,6 +126,11 @@ def wigner_subset_to_s2_jax(
             f"Fourier-Wigner algorithm does not support {sampling} sampling."
         )
 
+    if flmn.shape[1] != spins.shape[0]:
+        raise ValueError(
+            f"Number of spins specified {spins.shape[0]} does not match the number of Wigner coefficients {flmn.shape[1]}"
+        )
+
     # EXTRACT VARIOUS PRECOMPUTES
     Delta, _ = DW
 
@@ -167,10 +182,10 @@ def so3_to_wigner_subset(
     Transforms a signal on the rotation group to an arbitrary subset of its Wigner
     coefficients.
 
-        This function takes a signal on the rotation group SO(3) and computes a subset of
-        spin spherical harmonic coefficients corresponding to slices across the requested
-        spin numbers. These spin numbers can be arbitrarily chosen such that their absolute
-        value is less than or equal to the azimuthal band-limit :math:`N\leq L`.
+    This function takes a signal on the rotation group SO(3) and computes a subset of
+    spin spherical harmonic coefficients corresponding to slices across the requested
+    spin numbers. These spin numbers can be arbitrarily chosen such that their absolute
+    value is less than or equal to the azimuthal band-limit :math:`N\leq L`.
 
     Args:
         f (np.ndarray): Signal on the rotation group with shape :math:`[batch, n_\gamma, n_\theta,n_\phi, channels]`.
@@ -186,12 +201,11 @@ def so3_to_wigner_subset(
         np.ndarray: Collection of spin spherical harmonic coefficients with shape :math:`[batch, n_s, L, 2L-1, channels]`.
 
     """
-    # COMPUTE FFT OVER GAMMA
-    x = np.fft.fft(f, axis=-4, norm="forward")
-    x = np.fft.fftshift(x, axes=-4)
-
-    # EXTRACT REQUESTED SPIN COMPONENTS
-    x = x[:, N - 1 - spins]
+    # COMPUTE DFT OVER GAMMA SUBSET
+    e = np.exp(
+        -2j * np.pi * np.einsum("g,n->gn", np.arange(f.shape[1]) / f.shape[1], -spins)
+    )
+    x = np.einsum("bgtpc,gn->bntpc", f, e) / f.shape[1]
 
     return s2_to_wigner_subset(x, spins, DW, L, sampling)
 
@@ -209,10 +223,10 @@ def so3_to_wigner_subset_jax(
     Transforms a signal on the rotation group to an arbitrary subset of its Wigner
     coefficients (JAX).
 
-        This function takes a signal on the rotation group SO(3) and computes a subset of
-        spin spherical harmonic coefficients corresponding to slices across the requested
-        spin numbers. These spin numbers can be arbitrarily chosen such that their absolute
-        value is less than or equal to the azimuthal band-limit :math:`N\leq L`.
+    This function takes a signal on the rotation group SO(3) and computes a subset of
+    spin spherical harmonic coefficients corresponding to slices across the requested
+    spin numbers. These spin numbers can be arbitrarily chosen such that their absolute
+    value is less than or equal to the azimuthal band-limit :math:`N\leq L`.
 
     Args:
         f (jnp.ndarray): Signal on the rotation group with shape :math:`[batch, n_\gamma, n_\theta,n_\phi, channels]`.
@@ -229,12 +243,13 @@ def so3_to_wigner_subset_jax(
             with shape :math:`[batch, n_s, L, 2L-1, channels]`.
 
     """
-    # COMPUTE FFT OVER GAMMA
-    x = jnp.fft.fft(f, axis=-4, norm="forward")
-    x = jnp.fft.fftshift(x, axes=-4)
-
-    # EXTRACT REQUESTED SPIN COMPONENTS
-    x = x[:, N - 1 - spins]
+    # COMPUTE DFT OVER GAMMA SUBSET
+    e = jnp.exp(
+        -2j
+        * jnp.pi
+        * jnp.einsum("g,n->gn", jnp.arange(f.shape[1]) / f.shape[1], -spins)
+    )
+    x = jnp.einsum("bgtpc,gn->bntpc", f, e) / f.shape[1]
 
     return s2_to_wigner_subset_jax(x, spins, DW, L, sampling)
 
@@ -250,11 +265,11 @@ def s2_to_wigner_subset(
     Transforms from a collection of arbitrary spin signals on the sphere to the
     corresponding collection of their harmonic coefficients.
 
-        This function takes a multimodal collection of spin spherical harmonic signals
-        on the sphere and transforms them into their spin spherical harmonic coefficients.
-        These cofficients may then be combined into a subset of Wigner coefficients for
-        downstream analysis. In this way one may combine input features across a variety
-        of spins into a unified representation.
+    This function takes a multimodal collection of spin spherical harmonic signals
+    on the sphere and transforms them into their spin spherical harmonic coefficients.
+    These coefficients may then be combined into a subset of Wigner coefficients for
+    downstream analysis. In this way one may combine input features across a variety
+    of spins into a unified representation.
 
     Args:
         fs (np.ndarray): Collection of spin signal maps on the sphere with shape :math:`[batch, n_s, n_\theta,n_\phi, channels]`.
@@ -336,11 +351,11 @@ def s2_to_wigner_subset_jax(
     Transforms from a collection of arbitrary spin signals on the sphere to the
     corresponding collection of their harmonic coefficients (JAX).
 
-        This function takes a multimodal collection of spin spherical harmonic signals
-        on the sphere and transforms them into their spin spherical harmonic coefficients.
-        These cofficients may then be combined into a subset of Wigner coefficients for
-        downstream analysis. In this way one may combine input features across a variety
-        of spins into a unified representation.
+    This function takes a multimodal collection of spin spherical harmonic signals
+    on the sphere and transforms them into their spin spherical harmonic coefficients.
+    These coefficients may then be combined into a subset of Wigner coefficients for
+    downstream analysis. In this way one may combine input features across a variety
+    of spins into a unified representation.
 
     Args:
         fs (jnp.ndarray): Collection of spin signal maps on the sphere with shape :math:`[batch, n_s, n_\theta,n_\phi, channels]`.

tests/test_lifting_transforms.py

@@ -81,11 +81,7 @@ def test_custom_forward_from_so3(
     spins = -np.arange(-N + 1, N)
 
     # FUNCTION SWITCH
-    func = (
-        ops.so3_to_wigner_subset_jax
-        if method == "jax"
-        else ops.so3_to_wigner_subset_jax
-    )
+    func = ops.so3_to_wigner_subset_jax if method == "jax" else ops.so3_to_wigner_subset
 
     # CREATE CORRECT SHAPE (BATCH: 1, CHANNELS: 1)
     f = f.reshape((1,) + f.shape + (1,))