diff --git a/potpyri/instruments/MMIRS.py b/potpyri/instruments/MMIRS.py index b56e9b6..f573049 100755 --- a/potpyri/instruments/MMIRS.py +++ b/potpyri/instruments/MMIRS.py @@ -83,7 +83,7 @@ def __init__(self): self.bad_keywords = ['MOSID'] self.bad_values = ['closed'] - self.detrend = True + self.detrend = False self.catalog_zp = '2MASS' self.out_size = 2500 diff --git a/potpyri/instruments/instrument.py b/potpyri/instruments/instrument.py index 51acf7c..3a0a76c 100755 --- a/potpyri/instruments/instrument.py +++ b/potpyri/instruments/instrument.py @@ -525,14 +525,16 @@ def create_sky(self, sky_list, fil, amp, binn, paths, log=None, **kwargs): if log: log.info(f'Importing {sky}') sky_full = self.import_sci_image(sky, log=log) - mean, med, stddev = sigma_clipped_stats(sky_full.data) + mean, med, stddev = sigma_clipped_stats(sky_full.data, + sigma_upper=2.5, sigma_lower=3.5) # Mask outliers - mask = sky_full.data > med + 5 * stddev + mask = sky_full.data > med + 2.5 * stddev sky_full.data[mask]=np.nan # Normalize by median sky background - mean, med, stddev = sigma_clipped_stats(sky_full.data) + mean, med, stddev = sigma_clipped_stats(sky_full.data, + sigma_upper=2.5, sigma_lower=3.5) norm = 1./med sky_full = sky_full.multiply(norm) diff --git a/potpyri/primitives/image_procs.py b/potpyri/primitives/image_procs.py index 27c49fc..a07b54c 100755 --- a/potpyri/primitives/image_procs.py +++ b/potpyri/primitives/image_procs.py @@ -357,7 +357,10 @@ def image_proc(image_data, tel, paths, skip_skysub=False, sci_med = add_stack_mask(sci_med, aligned_data) if tel.detrend: + if log: log.info('Detrending stack') sci_med = detrend_stack(sci_med) + else: + if log: log.info('Skipping detrending') else: sci_med = fits.open(data_images[0]) @@ -426,12 +429,14 @@ def detrend_stack(stack): data = stack[0].data mask = stack[1].data.astype(bool) - mean, med, stddev = sigma_clipped_stats(data, mask=mask, axis=1) + mean, med, stddev = sigma_clipped_stats(data, mask=mask, axis=1, + sigma_upper=2.5) data = data - med[:,None] row_med = np.nanmedian(med) - mean, med, stddev = sigma_clipped_stats(data, mask=mask, axis=0) + mean, med, stddev = sigma_clipped_stats(data, mask=mask, axis=0, + sigma_upper=2.5) data = data - med[None,:] col_med = np.nanmedian(med) diff --git a/potpyri/primitives/solve_wcs.py b/potpyri/primitives/solve_wcs.py index ab387e9..d4e4718 100755 --- a/potpyri/primitives/solve_wcs.py +++ b/potpyri/primitives/solve_wcs.py @@ -335,7 +335,7 @@ def solve_astrometry(file, tel, binn, paths, radius=0.5, replace=True, return(False) def align_to_gaia(file, tel, radius=0.5, max_search_radius=5.0*u.arcsec, - save_centroids=False, min_gaia_match=5, log=None): + save_centroids=False, min_gaia_match=7, log=None): cat = get_gaia_catalog(file, log=log)