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Fix test warnings #266

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Merged
gmloose merged 2 commits into from
Oct 30, 2025
Merged

Fix test warnings #266

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f29d7bf
Fix ResourceWarning
gmloose Oct 30, 2025
6c021c1
Fix DeprecationWarning
gmloose Oct 30, 2025
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11 changes: 1 addition & 10 deletions bdsf/shapelets.py
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Original file line number Diff line number Diff line change
Expand Up @@ -86,16 +86,7 @@ def shapelet_image(basis, beta, centre, hc, nx, ny, size):
order nx,ny on an image of size size. Does what getcartim.f does in fBDSM. nx,ny -> 0-nmax
Centre is by Python convention, for retards who count from zero. """
from math import sqrt,pi
try:
from scipy import factorial
except ImportError:
try:
from scipy.misc.common import factorial
except ImportError:
try:
from scipy.misc import factorial
except ImportError:
from scipy.special import factorial
from scipy.special import factorial

hcx = hc[nx,:]
hcy = hc[ny,:]
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20 changes: 10 additions & 10 deletions test/compare_outputs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -229,7 +229,7 @@ def __init__(self, imagefile):
self.shift = 0.
self.noise = 1.

self.header = astropy.io.fits.open(imagefile)[0].header
self.header = astropy.io.fits.getheader(imagefile)
self.find_beam()
self.find_freq()
self.flatten()
Expand Down Expand Up @@ -269,16 +269,16 @@ def find_freq(self):

def flatten(self):
""" Flatten a fits file so that it becomes a 2D image. Return new header and data """
f = astropy.io.fits.open(self.imagefile)
fits_data = astropy.io.fits.getdata(self.imagefile)

naxis = f[0].header['NAXIS']
naxis = self.header['NAXIS']
if naxis < 2:
raise RuntimeError('Can\'t make map from this')
if naxis == 2:
self.img_hdr = f[0].header
self.img_data = f[0].data
self.img_hdr = self.header
self.img_data = fits_data
else:
w = astropy.wcs.WCS(f[0].header)
w = astropy.wcs.WCS(self.header)
wn = astropy.wcs.WCS(naxis=2)
wn.wcs.crpix[0] = w.wcs.crpix[0]
wn.wcs.crpix[1] = w.wcs.crpix[1]
Expand All @@ -289,16 +289,16 @@ def flatten(self):

header = wn.to_header()
header["NAXIS"] = 2
header["NAXIS1"] = f[0].header['NAXIS1']
header["NAXIS2"] = f[0].header['NAXIS2']
header["NAXIS1"] = self.header['NAXIS1']
header["NAXIS2"] = self.header['NAXIS2']
header["FREQ"] = self.freq
header['RESTFREQ'] = self.freq
header['BMAJ'] = self.beam[0]
header['BMIN'] = self.beam[1]
header['BPA'] = self.beam[2]
copy = ('EQUINOX', 'EPOCH')
for k in copy:
r = f[0].header.get(k)
r = self.header.get(k)
if r:
header[k] = r

Expand All @@ -309,7 +309,7 @@ def flatten(self):
else:
dataslice.append(0)
self.img_hdr = header
self.img_data = f[0].data[tuple(dataslice)]
self.img_data = fits_data[tuple(dataslice)]
self.min_value = float(np.nanmin(self.img_data))
self.max_value = float(np.nanmax(self.img_data))
self.mean_value = float(np.nanmean(self.img_data))
Expand Down