diff options
| -rwxr-xr-x | astro/fits/fitscube.py | 2 | ||||
| -rwxr-xr-x | astro/fits/fitsimage.py | 20 |
2 files changed, 12 insertions, 10 deletions
diff --git a/astro/fits/fitscube.py b/astro/fits/fitscube.py index bd44ce7..976e690 100755 --- a/astro/fits/fitscube.py +++ b/astro/fits/fitscube.py @@ -415,7 +415,7 @@ def cmd_corrupt(args): def main(): parser = argparse.ArgumentParser( - description="Create FITS cube from a series of image slices.") + description="FITS image cube manipulation tool") subparsers = parser.add_subparsers(dest="subparser_name", title="sub-commands", help="additional help") diff --git a/astro/fits/fitsimage.py b/astro/fits/fitsimage.py index 74b03cf..186e09b 100755 --- a/astro/fits/fitsimage.py +++ b/astro/fits/fitsimage.py @@ -78,24 +78,26 @@ def cmd_info(args): fimage = FITSImage(args.infile) print("Image data shape: {0}".format(fimage.shape)) print("Data unit: %s" % fimage.bunit) - image = fimage.image + data = fimage.image if args.abs: - image = np.abs(image) + data = np.abs(data) if args.center: print("Central box size: %d" % args.center) - rows, cols = image.shape + rows, cols = data.shape rc, cc = rows//2, cols//2 cs1, cs2 = args.center//2, (args.center+1)//2 - image = image[(rc-cs1):(rc+cs2), (cc-cs1):(cc+cs2)] - mean = np.mean(image) - median = np.median(image) - iqr = np.diff(np.percentile(image, q=(25, 75))) - std = np.std(image) - rms = np.sqrt(np.mean(image**2)) + data = data[(rc-cs1):(rc+cs2), (cc-cs1):(cc+cs2)] + mean = np.mean(data) + median = np.median(data) + std = np.std(data) + iqr = np.diff(np.percentile(data, q=(25, 75))) + mad = np.median(np.abs(data - median)) + rms = np.sqrt(np.mean(data**2)) print("mean: %-12.6e" % mean) print("median: %-12.6e" % median) print("std: %-12.6e (standard deviation)" % std) print("iqr: %-12.6e (interquartile range)" % iqr) + print("mad: %-12.6e (median absolute deviation)" % mad) print("rms: %-12.6e (root-mean-squared)" % rms) |