Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Feature/precompute transform #76

Merged
merged 2 commits into from
Sep 27, 2023
Merged

Feature/precompute transform #76

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
8db5716
add interfacing for s2fft precompute transforms
CosmoMatt Apr 4, 2023
0d905c8
update jax precompute functionality
CosmoMatt Apr 5, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 1 addition & 2 deletions s2wav/transforms/__init__.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,3 @@
from . import numpy_wavelets
from . import numpy_scattering
from . import jax_wavelets
from . import jax_scattering
from . import jax_wavelets_precompute
274 changes: 0 additions & 274 deletions s2wav/transforms/jax_scattering.py
View file
Open in desktop

This file was deleted.

12 changes: 3 additions & 9 deletions s2wav/transforms/jax_wavelets.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -63,7 +63,7 @@ def generate_wigner_precomputes(
return precomps


@partial(jit, static_argnums=(2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13))
# @partial(jit, static_argnums=(2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13))
def synthesis(
f_wav: jnp.ndarray,
f_scal: jnp.ndarray,
Expand Down Expand Up @@ -177,7 +177,7 @@ def synthesis(
return s2fft.inverse_jax(flm, L, spin, nside, sampling, reality)


@partial(jit, static_argnums=(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12))
# @partial(jit, static_argnums=(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12))
def analysis(
f: jnp.ndarray,
L: int,
Expand All @@ -193,7 +193,6 @@ def analysis(
filters: Tuple[jnp.ndarray] = None,
spmd: bool = False,
precomps: List[List[jnp.ndarray]] = None,
scattering: bool = False,
) -> Tuple[jnp.ndarray]:
r"""Wavelet analysis from pixel space to wavelet space for complex signals.

Expand Down Expand Up @@ -233,9 +232,6 @@ def analysis(
precomps (List[jnp.ndarray]): Precomputed list of recursion coefficients. At most
of length :math:`L^2`, which is a minimal memory overhead.

scattering (bool, optional): If using for scattering transform return absolute value
of scattering coefficients.

Returns:
f_wav (jnp.ndarray): Array of wavelet pixel-space coefficients
with shape :math:`[n_{J}, 2N-1, n_{\theta}, n_{\phi}]`.
Expand Down Expand Up @@ -293,8 +289,6 @@ def analysis(
spmd_iter,
L0j,
)
if scattering:
f_wav[j - J_min] = jnp.abs(f_wav[j - J_min])

# Project all harmonic coefficients for each lm onto scaling coefficients
phi = filters[1][:Ls] * jnp.sqrt(4 * jnp.pi / (2 * jnp.arange(Ls) + 1))
Expand All @@ -306,7 +300,7 @@ def analysis(
f_scal = temp * jnp.sqrt(1 / (4 * jnp.pi))
else:
f_scal = s2fft.inverse_jax(temp, Ls, spin, nside, sampling, reality)
return f_wav, jnp.real(f_scal) if reality else f_scal
return f_wav, f_scal


@partial(jit, static_argnums=(1, 2, 3, 4, 5, 6, 7, 8, 9, 11))
Expand Down
Loading
Loading