def plot_set( fits_list, name ) :
images = load_images( fits_list )
fig, axes = plt.subplots(nrows=len(images)/2, ncols=2)
for ax, data in zip(axes.flat,images) :
im = ax.imshow( data )
fig.subplots_adjust(right=0.9)
plt.savefig(name)
def plot_set(fits_list, name, labels=None, cmap_name='viridis', ncols=2):
images = load_images(fits_list)
print[image.shape for image in images]
images = [normalized_positive_image(image) for image in images]
fig, axes = plt.subplots(nrows=len(images) / ncols, ncols=ncols)
if labels != None:
for ax, data, label in zip(axes.flat, images, labels):
if args['hog'] != None: data = hog_image(data, label)
im = ax.imshow(data, cmap=plt.get_cmap(cmap_name))
if len(label) > 6:
plt.text(0.1,
0.9,
'%.2f' % float(label),
ha='left',
va='center',
transform=ax.transAxes,
fontsize='large',
color='white')
else:
plt.text(0.1,
0.9,
label,
ha='left',
va='center',
transform=ax.transAxes,
fontsize='large',
color='white')
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
else:
for ax, data in zip(axes.flat, images):
im = ax.imshow(data, cmap=plt.get_cmap(cmap_name))
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
#plt.subplots_adjust(wspace=-0.8, hspace=-0.4)
plt.subplots_adjust(wspace=-0.4, hspace=-0.4)
print "saving " + name
plt.tight_layout()
plt.savefig(name, bbox_inches='tight', pad_inches=0)
def data2plot(fitsfiles, name):
fitsdata = load_images(fitsfiles)
nrows = len(fitsfiles) / 2
return name, nrows, fitsdata, [
hog(fd, visualise=True, **read_hog_kwargs(modeldir)) for fd in fitsdata
]
def data2plot( fitsfiles, name ) :
fitsdata = load_images(fitsfiles)
nrows = len(fitsfiles)/2
return name, nrows, fitsdata, [hog(fd, visualise=True, **read_hog_kwargs(modeldir)) for fd in fitsdata]