/usr/lib/python3/dist-packages/photutils/aperture/circle.py is in python3-photutils 0.3-3.
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from __future__ import (absolute_import, division, print_function,
unicode_literals)
import math
import numpy as np
from astropy.coordinates import SkyCoord
import astropy.units as u
from astropy.wcs.utils import skycoord_to_pixel
from .core import (PixelAperture, SkyAperture, ApertureMask,
_sanitize_pixel_positions, _translate_mask_method,
_make_annulus_path)
from ..geometry import circular_overlap_grid
from ..utils.wcs_helpers import (skycoord_to_pixel_scale_angle,
assert_angle_or_pixel)
__all__ = ['CircularMaskMixin', 'CircularAperture', 'CircularAnnulus',
'SkyCircularAperture', 'SkyCircularAnnulus']
class CircularMaskMixin(object):
"""
Mixin class to create masks for circular and circular-annulus
aperture objects.
"""
def to_mask(self, method='exact', subpixels=5):
"""
Return a list of `ApertureMask` objects, one for each aperture
position.
Parameters
----------
method : {'exact', 'center', 'subpixel'}, optional
The method used to determine the overlap of the aperture on
the pixel grid. Not all options are available for all
aperture types. Note that the more precise methods are
generally slower. The following methods are available:
* ``'exact'`` (default):
The the exact fractional overlap of the aperture and
each pixel is calculated. The returned mask will
contain values between 0 and 1.
* ``'center'``:
A pixel is considered to be entirely in or out of the
aperture depending on whether its center is in or out
of the aperture. The returned mask will contain
values only of 0 (out) and 1 (in).
* ``'subpixel'``:
A pixel is divided into subpixels (see the
``subpixels`` keyword), each of which are considered
to be entirely in or out of the aperture depending on
whether its center is in or out of the aperture. If
``subpixels=1``, this method is equivalent to
``'center'``. The returned mask will contain values
between 0 and 1.
subpixels : int, optional
For the ``'subpixel'`` method, resample pixels by this factor
in each dimension. That is, each pixel is divided into
``subpixels ** 2`` subpixels.
Returns
-------
mask : list of `~photutils.ApertureMask`
A list of aperture mask objects.
"""
if method not in ('center', 'subpixel', 'exact'):
raise ValueError('"{0}" method is not available for this '
'aperture.'.format(method))
use_exact, subpixels = _translate_mask_method(method, subpixels)
if hasattr(self, 'r'):
radius = self.r
elif hasattr(self, 'r_out'): # annulus
radius = self.r_out
else:
raise ValueError('Cannot determine the aperture radius.')
masks = []
for position, _slice, _geom_slice in zip(self.positions, self._slices,
self._geom_slices):
px_min, px_max = _geom_slice[1].start, _geom_slice[1].stop
py_min, py_max = _geom_slice[0].start, _geom_slice[0].stop
dx = px_max - px_min
dy = py_max - py_min
mask = circular_overlap_grid(px_min, px_max, py_min, py_max,
dx, dy, radius, use_exact, subpixels)
if hasattr(self, 'r_in'): # annulus
mask -= circular_overlap_grid(px_min, px_max, py_min, py_max,
dx, dy, self.r_in, use_exact,
subpixels)
masks.append(ApertureMask(mask, _slice))
return masks
class CircularAperture(CircularMaskMixin, PixelAperture):
"""
Circular aperture(s), defined in pixel coordinates.
Parameters
----------
positions : array_like or `~astropy.units.Quantity`
Pixel coordinates of the aperture center(s) in one of the
following formats:
* single ``(x, y)`` tuple
* list of ``(x, y)`` tuples
* ``Nx2`` or ``2xN`` `~numpy.ndarray`
* ``Nx2`` or ``2xN`` `~astropy.units.Quantity` in pixel units
Note that a ``2x2`` `~numpy.ndarray` or
`~astropy.units.Quantity` is interpreted as ``Nx2``, i.e. two
rows of (x, y) coordinates.
r : float
The radius of the aperture(s), in pixels.
Raises
------
ValueError : `ValueError`
If the input radius, ``r``, is negative.
"""
def __init__(self, positions, r):
try:
self.r = float(r)
except TypeError:
raise TypeError('r must be numeric, received {0}'.format(type(r)))
if r < 0:
raise ValueError('r must be non-negative')
self.positions = _sanitize_pixel_positions(positions)
# TODO: make lazyproperty?, but update if positions or radius change
@property
def _slices(self):
x_min = np.floor(self.positions[:, 0] - self.r + 0.5).astype(int)
x_max = np.floor(self.positions[:, 0] + self.r + 1.5).astype(int)
y_min = np.floor(self.positions[:, 1] - self.r + 0.5).astype(int)
y_max = np.floor(self.positions[:, 1] + self.r + 1.5).astype(int)
return [(slice(ymin, ymax), slice(xmin, xmax))
for xmin, xmax, ymin, ymax in zip(x_min, x_max, y_min, y_max)]
# TODO: make lazyproperty?, but update if positions or radius change
def area(self):
return math.pi * self.r ** 2
def plot(self, origin=(0, 0), indices=None, ax=None, fill=False,
**kwargs):
import matplotlib.patches as mpatches
plot_positions, ax, kwargs = self._prepare_plot(
origin, indices, ax, fill, **kwargs)
for position in plot_positions:
patch = mpatches.Circle(position, self.r, **kwargs)
ax.add_patch(patch)
class CircularAnnulus(CircularMaskMixin, PixelAperture):
"""
Circular annulus aperture(s), defined in pixel coordinates.
Parameters
----------
positions : array_like or `~astropy.units.Quantity`
Pixel coordinates of the aperture center(s) in one of the
following formats:
* single ``(x, y)`` tuple
* list of ``(x, y)`` tuples
* ``Nx2`` or ``2xN`` `~numpy.ndarray`
* ``Nx2`` or ``2xN`` `~astropy.units.Quantity` in pixel units
Note that a ``2x2`` `~numpy.ndarray` or
`~astropy.units.Quantity` is interpreted as ``Nx2``, i.e. two
rows of (x, y) coordinates.
r_in : float
The inner radius of the annulus.
r_out : float
The outer radius of the annulus.
Raises
------
ValueError : `ValueError`
If inner radius (``r_in``) is greater than outer radius (``r_out``).
ValueError : `ValueError`
If inner radius (``r_in``) is negative.
"""
def __init__(self, positions, r_in, r_out):
try:
self.r_in = r_in
self.r_out = r_out
except TypeError:
raise TypeError("'r_in' and 'r_out' must be numeric, received "
"{0} and {1}".format((type(r_in), type(r_out))))
if not (r_out > r_in):
raise ValueError('r_out must be greater than r_in')
if r_in < 0:
raise ValueError('r_in must be non-negative')
self.positions = _sanitize_pixel_positions(positions)
@property
def _slices(self):
x_min = np.floor(self.positions[:, 0] - self.r_out + 0.5).astype(int)
x_max = np.floor(self.positions[:, 0] + self.r_out + 1.5).astype(int)
y_min = np.floor(self.positions[:, 1] - self.r_out + 0.5).astype(int)
y_max = np.floor(self.positions[:, 1] + self.r_out + 1.5).astype(int)
return [(slice(ymin, ymax), slice(xmin, xmax))
for xmin, xmax, ymin, ymax in zip(x_min, x_max, y_min, y_max)]
def area(self):
return math.pi * (self.r_out ** 2 - self.r_in ** 2)
def plot(self, origin=(0, 0), indices=None, ax=None, fill=False,
**kwargs):
import matplotlib.patches as mpatches
plot_positions, ax, kwargs = self._prepare_plot(
origin, indices, ax, fill, **kwargs)
resolution = 20
for position in plot_positions:
patch_inner = mpatches.CirclePolygon(position, self.r_in,
resolution=resolution)
patch_outer = mpatches.CirclePolygon(position, self.r_out,
resolution=resolution)
path = _make_annulus_path(patch_inner, patch_outer)
patch = mpatches.PathPatch(path, **kwargs)
ax.add_patch(patch)
class SkyCircularAperture(SkyAperture):
"""
Circular aperture(s), defined in sky coordinates.
Parameters
----------
positions : `~astropy.coordinates.SkyCoord`
Celestial coordinates of the aperture center(s). This can be
either scalar coordinates or an array of coordinates.
r : `~astropy.units.Quantity`
The radius of the aperture(s), either in angular or pixel units.
"""
def __init__(self, positions, r):
if isinstance(positions, SkyCoord):
self.positions = positions
else:
raise TypeError('positions must be a SkyCoord object.')
assert_angle_or_pixel('r', r)
self.r = r
def to_pixel(self, wcs, mode='all'):
"""
Convert the aperture to a `CircularAperture` instance in pixel
coordinates.
Parameters
----------
wcs : `~astropy.wcs.WCS`
The WCS transformation to use.
mode : {'all', 'wcs'}, optional
Whether to do the transformation including distortions
(``'all'``; default) or only including only the core WCS
transformation (``'wcs'``).
Returns
-------
aperture : `CircularAperture` object
A `CircularAperture` object.
"""
x, y = skycoord_to_pixel(self.positions, wcs, mode=mode)
if self.r.unit.physical_type == 'angle':
central_pos = SkyCoord([wcs.wcs.crval], frame=self.positions.name,
unit=wcs.wcs.cunit)
xc, yc, scale, angle = skycoord_to_pixel_scale_angle(central_pos,
wcs)
r = (scale * self.r).to(u.pixel).value
else: # pixels
r = self.r.value
pixel_positions = np.array([x, y]).transpose()
return CircularAperture(pixel_positions, r)
class SkyCircularAnnulus(SkyAperture):
"""
Circular annulus aperture(s), defined in sky coordinates.
Parameters
----------
positions : `~astropy.coordinates.SkyCoord`
Celestial coordinates of the aperture center(s). This can be
either scalar coordinates or an array of coordinates.
r_in : `~astropy.units.Quantity`
The inner radius of the annulus, either in angular or pixel
units.
r_out : `~astropy.units.Quantity`
The outer radius of the annulus, either in angular or pixel
units.
"""
def __init__(self, positions, r_in, r_out):
if isinstance(positions, SkyCoord):
self.positions = positions
else:
raise TypeError("positions should be a SkyCoord instance")
assert_angle_or_pixel('r_in', r_in)
assert_angle_or_pixel('r_out', r_out)
if r_in.unit.physical_type != r_out.unit.physical_type:
raise ValueError("r_in and r_out should either both be angles "
"or in pixels")
self.r_in = r_in
self.r_out = r_out
def to_pixel(self, wcs, mode='all'):
"""
Convert the aperture to a `CircularAnnulus` instance in pixel
coordinates.
Parameters
----------
wcs : `~astropy.wcs.WCS`
The WCS transformation to use.
mode : {'all', 'wcs'}, optional
Whether to do the transformation including distortions
(``'all'``; default) or only including only the core WCS
transformation (``'wcs'``).
Returns
-------
aperture : `CircularAnnulus` object
A `CircularAnnulus` object.
"""
x, y = skycoord_to_pixel(self.positions, wcs, mode=mode)
if self.r_in.unit.physical_type == 'angle':
central_pos = SkyCoord([wcs.wcs.crval], frame=self.positions.name,
unit=wcs.wcs.cunit)
xc, yc, scale, angle = skycoord_to_pixel_scale_angle(central_pos,
wcs)
r_in = (scale * self.r_in).to(u.pixel).value
r_out = (scale * self.r_out).to(u.pixel).value
else: # pixels
r_in = self.r_in.value
r_out = self.r_out.value
pixel_positions = np.array([x, y]).transpose()
return CircularAnnulus(pixel_positions, r_in, r_out)
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