From 47d7cd18a3ddb5584227cc3483977aae85e54736 Mon Sep 17 00:00:00 2001 From: anschaible Date: Wed, 1 Apr 2026 09:02:49 +0200 Subject: [PATCH 1/2] fix noise module, change to jnp.nanmeadian --- .gitignore | 1 + rubix/telescope/noise/noise.py | 5 +++-- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/.gitignore b/.gitignore index 675b2d8..dba8556 100644 --- a/.gitignore +++ b/.gitignore @@ -159,6 +159,7 @@ notebooks/frames rubix/**/*.ipynb rubix/spectra/ssp/templates/fsps.h5 +rubix/spectra/ssp/templates/* rubix/spectra/ssp/templates/*.gz rubix/spectra/ssp/templates/*fits.gz rubix/spectra/cue/cue/* diff --git a/rubix/telescope/noise/noise.py b/rubix/telescope/noise/noise.py index 3f7af5b..3d7f1a0 100644 --- a/rubix/telescope/noise/noise.py +++ b/rubix/telescope/noise/noise.py @@ -58,8 +58,9 @@ def calculate_S2N( nonzero_mask = flux_image > 0 # Calculate the median flux value where the flux is non-zero - median_flux = jnp.median(jnp.where(nonzero_mask, flux_image, jnp.nan)) - median_flux = jnp.nan_to_num(median_flux, nan=0.0) + #median_flux = jnp.median(jnp.where(nonzero_mask, flux_image, jnp.nan)) + #median_flux = jnp.nan_to_num(median_flux, nan=0.0) + median_flux = jnp.nanmedian(jnp.where(nonzero_mask, flux_image, jnp.nan)) # Calculate the noise factor noise_factor = jnp.sqrt(median_flux) / observation_signal_to_noise From 33cb6fcfb078be99e0b5d3efa75f92e83fb111db Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Wed, 1 Apr 2026 07:04:19 +0000 Subject: [PATCH 2/2] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- rubix/telescope/noise/noise.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/rubix/telescope/noise/noise.py b/rubix/telescope/noise/noise.py index 3d7f1a0..6559d41 100644 --- a/rubix/telescope/noise/noise.py +++ b/rubix/telescope/noise/noise.py @@ -58,8 +58,8 @@ def calculate_S2N( nonzero_mask = flux_image > 0 # Calculate the median flux value where the flux is non-zero - #median_flux = jnp.median(jnp.where(nonzero_mask, flux_image, jnp.nan)) - #median_flux = jnp.nan_to_num(median_flux, nan=0.0) + # median_flux = jnp.median(jnp.where(nonzero_mask, flux_image, jnp.nan)) + # median_flux = jnp.nan_to_num(median_flux, nan=0.0) median_flux = jnp.nanmedian(jnp.where(nonzero_mask, flux_image, jnp.nan)) # Calculate the noise factor