def get_context_data(self, **kwargs):
context = super(ImagePlot, self).get_context_data(**kwargs)
context['sources'] = self.object.extractedsources.all()
try:
context['size'] = int(self.request.GET.get('size', 5))
except ValueError:
context['size'] = 5
context['hdu'] = get_hdu(self.object.url)
return context
def get_context_data(self, **kwargs):
context = super(ImagePlot, self).get_context_data(**kwargs)
context['sources'] = self.object.extractedsources.all()
try:
context['size'] = int(self.request.GET.get('size', 5))
except ValueError:
context['size'] = 5
context['hdu'] = get_hdu(self.object.url)
return context
def extracted_sources_pixels(image, size):
"""
:param image: a banana.models.Image object
:returns: a list of sources of an image
"""
hdu = get_hdu(image.url)
if not hdu:
return None
# make an image
fig = pyplot.figure(figsize=(size, size))
plot = aplpy.FITSFigure(hdu, figure=fig, subplot=[0, 0, 1, 1],
auto_refresh=False)
# get source info from database
sources = image.extractedsources.all()
ids = [source.id for source in sources]
# If the image has a reference declination pointing to the north
# celestial pole (ie, CRVAL2=90), our APLpy will incorrectly plot them
# with an RA 180 degrees wrong. We rotate them back here. See Trap
# issue #4599 for (much) more discussion.
if "CRVAL2" in hdu[0].header and hdu[0].header["CRVAL2"] == 90:
x_world = [(source.ra + 180) % 360 for source in sources]
else:
x_world = [source.ra for source in sources]
y_world = [source.decl for source in sources]
w_world = numpy.array([source.semimajor / 900 for source in sources])
h_world = numpy.array([source.semiminor / 900 for source in sources])
# first convert positions to matplotlib image coordinates
x_plot, y_plot = plot.world2pixel(x_world, y_world)
arcperpix = aplpy.wcs_util.arcperpix(plot._wcs)
w_plot = 3600.0 * w_world / arcperpix
h_plot = 3600.0 * h_world / arcperpix
# then transform them to true pixel coordinates
ax = fig.axes[0]
xy_pixels = ax.transData.transform(numpy.vstack([x_plot, y_plot]).T)
x_px, y_px = xy_pixels.T
# In matplotlib, 0,0 is the lower left corner, whereas it's usually the
# upper right for most image software, so we'll flip the y-coords
fig_width, fig_height = fig.canvas.get_width_height()
y_px = fig_height - y_px
# because of an unknown reason we need to scale the coordinates with 25%
y_px *= 1.25
x_px *= 1.25
# create average size since areamap can only draw circles
size_px = (w_plot + h_plot) / 4
return zip(ids, list(x_px), list(y_px), list(size_px))
def extracted_sources_pixels(image, size):
"""
:param image: a banana.models.Image object
:returns: a list of sources of an image
"""
hdu = get_hdu(image.url)
if not hdu:
return None
# make an image
fig = pyplot.figure(figsize=(size, size))
plot = aplpy.FITSFigure(hdu,
figure=fig,
subplot=[0, 0, 1, 1],
auto_refresh=False)
# get source info from database
sources = image.extractedsources.all()
ids = [source.id for source in sources]
x_world = numpy.array([source.ra for source in sources])
y_world = numpy.array([source.decl for source in sources])
w_world = numpy.array([source.semimajor / 900 for source in sources])
h_world = numpy.array([source.semiminor / 900 for source in sources])
# first convert positions to matplotlib image coordinates
x_plot, y_plot = plot.world2pixel(x_world, y_world)
arcperpix = aplpy.wcs_util.arcperpix(plot._wcs)
w_plot = 3600.0 * w_world / arcperpix
h_plot = 3600.0 * h_world / arcperpix
# then transform them to true pixel coordinates
ax = fig.axes[0]
xy_pixels = ax.transData.transform(numpy.vstack([x_plot, y_plot]).T)
x_px, y_px = xy_pixels.T
# In matplotlib, 0,0 is the lower left corner, whereas it's usually the
# upper right for most image software, so we'll flip the y-coords
fig_width, fig_height = fig.canvas.get_width_height()
y_px = fig_height - y_px
# because of an unknown reason we need to scale the coordinates with 25%
y_px *= 1.25
x_px *= 1.25
# create average size since areamap can only draw circles
size_px = (w_plot + h_plot) / 4
return zip(ids, list(x_px), list(y_px), list(size_px))
def extracted_sources_pixels(image, size):
"""
:param image: a banana.models.Image object
:returns: a list of sources of an image
"""
hdu = get_hdu(image.url)
if not hdu:
return None
# make an image
fig = pyplot.figure(figsize=(size, size))
plot = aplpy.FITSFigure(hdu, figure=fig, subplot=[0, 0, 1, 1],
auto_refresh=False)
# get source info from database
sources = image.extractedsources.all()
ids = [source.id for source in sources]
x_world = numpy.array([source.ra for source in sources])
y_world = numpy.array([source.decl for source in sources])
w_world = numpy.array([source.semimajor / 900 for source in sources])
h_world = numpy.array([source.semiminor / 900 for source in sources])
# first convert positions to matplotlib image coordinates
x_plot, y_plot = plot.world2pixel(x_world, y_world)
arcperpix = aplpy.wcs_util.arcperpix(plot._wcs)
w_plot = 3600.0 * w_world / arcperpix
h_plot = 3600.0 * h_world / arcperpix
# then transform them to true pixel coordinates
ax = fig.axes[0]
xy_pixels = ax.transData.transform(numpy.vstack([x_plot, y_plot]).T)
x_px, y_px = xy_pixels.T
# In matplotlib, 0,0 is the lower left corner, whereas it's usually the
# upper right for most image software, so we'll flip the y-coords
fig_width, fig_height = fig.canvas.get_width_height()
y_px = fig_height - y_px
# because of an unknown reason we need to scale the coordinates with 25%
y_px *= 1.25
x_px *= 1.25
# create average size since areamap can only draw circles
size_px = (w_plot + h_plot) / 4
return zip(ids, list(x_px), list(y_px), list(size_px))
def get_context_data(self, **kwargs):
context = super(ExtractedSourcePlot, self).get_context_data(**kwargs)
context['size'] = int(self.request.GET.get('size', 1))
context['hdu'] = get_hdu(self.object.image.url)
return context
def get_context_data(self, **kwargs):
context = super(ExtractedSourcePlot, self).get_context_data(**kwargs)
context['size'] = int(self.request.GET.get('size', 1))
context['hdu'] = get_hdu(self.object.image.url)
return context
