def extract_posvel_angle(hdu, p1, angle, header=None, gauss_width=2):
"""
Given a hdu in vlm format, and one position (in pixel
coordinates), and an angle, obtains a position velocity cut about
that position with that angle, along that line
Returns p-v image as a pyfits hdu unit.
@param hdu: input pyfits style HDU (header data unit) or just the numpy
numpy format data cube from pyfits HDU data attribute.
If numpy format data cube is passed, then the header parameter
should also be passed in. The cube is expected to be in vlm format.
@type hdu: pyfits hdu type or numpy nd-array
@param p1: (x, y) pixel location of position 1. The x,y position can be a
two-tuple, a list of two elements, or numpy array of two elements
@type p1: tuple, list or array of floats or ints
@param angle: angle of PV cut with respect to X-axis in degrees
@type angle: float
@param header: pyfits header object if needed
@gauss_width: the width of the gaussian kernel to use in weighting
neighboring pixels with when extracting spectra
@type gauss_width: int
@return A HDU instance with 2d position-velocity image in the data
attribute of the HDU, and the corresponding header in header
attribute of the HDU.
"""
if isinstance(hdu, astropy.io.fits.hdu.image.PrimaryHDU):
#get data and header from the hdu
data = hdu.data
header = hdu.header
elif isinstance(hdu, numpy.ndarray):
if header is None or not isinstance(header, astropy.io.fits.header.Header):
raise SculptArgumentError('header', "Since you passed in data that is a numpy array, set header to a pyfits header type")
data = hdu
else:
raise SculptArgumentError('hdu', "can only be one of pyfits.PrimaryHDU type or numpy ndarray")
hdr = header.copy()
dt = data.copy()
hdu = pyfits.PrimaryHDU(dt, header=hdr)
if gauss_width <= 0 or type(gauss_width) != types.IntType:
raise SculptArgumentError('gauss_width', "should be positive and non-zero integer")
try:
if len(p1) != 2:
raise SculptArgumentError('positions', "Positions p1 and p2 should be 2-element tuples, lists or arrays")
except:
raise SculptArgumentError('positions', "Positions p1 and p2 should be 2-element tuples, lists or arrays")
a, b = p1
#x2, y2 = p2
m = math.tan(math.radians(angle)) #slope of line
xmin, ymin = 0, 0
y1, x1, v1 = hdu.data.shape
ymax = y1-1
xmax = x1-1
print "xylims: ", xmin, ymin, xmax, ymax
# #check for x-limits first
# xl = None
# xh = None
# if m > 0.0:
# #line sloped right of vertical
# yl = m*(xmin-a) + b
# else:
# #line sloped left of vertical
# yl = m*(xmax-a) + b
# if ymin <= yl and yl <= ymax:
# if m > 0.0:
# xl = xmin
# else:
# xl = xmax
# if m > 0.0:
# yh = m*(xmax-a) + b
# else:
# yh = m*(xmin-a) + b
# print "yl, yh = ", yl, yh
# if ymin <= yh and yh <= ymax:
# if m > 0.0:
# xh = xmax
# else:
# xh = xmin
# if xl is None:
# yl = None
# if m > 0.0:
# xl = ((ymin-b)/m) + a
# else:
# xl = ((ymax-b)/m) + a
# if xmin <= xl and xl <= xmax:
# yl = ymin
# if xh is None:
# yh = None
# if m > 0.0:
# xh = ((ymax-b)/m) + a
# else:
# xh = ((ymin-b)/m) + a
# if xmin <= xh and xh <= xmax:
# yh = ymax
i1, i2 = line_rectangle_intersection(xmin, xmax, ymin, ymax, a, b, angle)
xl,yl = i1
xh,yh = i2
print xl, xh, yl, yh
d = math.sqrt((xl-xh)**2 + (yl-yh)**2.)
posvel = numpy.zeros((int(d), dt.shape[2]), dtype='float')
dist = numpy.arange(int(d))
if xl <= xh:
x = xl + numpy.sqrt(dist**2./(1+m**2.)) #2nd term is deltax
else:
x = xl - numpy.sqrt(dist**2./(1+m**2.)) #2nd term is deltax
y = yl + m*(x-xl)
for i in range(int(d)):
posvel[i,:] = extract_spec(hdu, x[i], y[i],
gauss_width=gauss_width).data
r, d = xyad(header, a, b)
sxaddpar(hdr, "CRVAL2", r)
dmid = math.sqrt((xl-a)**2 + (yl-b)**2)
sxaddpar(hdr, "CRPIX2", int(dmid))
sxaddpar(hdr, "NAXIS", 2)
sxdelpar(hdr, "NAXIS3")
for name in ('CTYPE', 'CRVAL', 'CDELT', 'CRPIX'):
sxdelpar(hdr, "%s3" % name)
sxaddhist(hdr, "Extracted posvel image from (%.1f, %.1f) with angle %.2f with gauss_width=%s" % (a, b, angle, gauss_width))
return pyfits.PrimaryHDU(posvel, header=hdr)
def extract_posvel(hdu, p1, p2, header=None, gauss_width=2):
"""
Given a hdu in vlm format, and two positions (in pixel
coordinates), obtains a position velocity cut along that line
Returns p-v image as a pyfits hdu unit.
@param hdu: input pyfits style HDU (header data unit) or just the numpy
numpy format data cube from pyfits HDU data attribute.
If numpy format data cube is passed, then the header parameter
should also be passed in. The cube is expected to be in vlm format.
@type hdu: pyfits hdu type or numpy nd-array
@param p1: (x, y) pixel location of position 1. The x,y position can be a
two-tuple, a list of two elements, or numpy array of two elements
@type p1: tuple, list or array of floats or ints
@param p2: (x, y) pixel location of position 2. The x,y position can be a
two-tuple, a list of two elements, or numpy array of two elements
@type p2: tuple, list or array of floats or ints
@param header: pyfits header object if needed
@gauss_width: the width of the gaussian kernel to use in weighting
neighboring pixels with when extracting spectra
@type gauss_width: int
@return A HDU instance with 2d position-velocity image in the data
attribute of the HDU, and the corresponding header in header
attribute of the HDU.
"""
if isinstance(hdu, astropy.io.fits.hdu.image.PrimaryHDU):
#get data and header from the hdu
data = hdu.data
header = hdu.header
elif isinstance(hdu, numpy.ndarray):
if header is None or not isinstance(header, astropy.io.fits.header.Header):
raise SculptArgumentError('header', "Since you passed in data that is a numpy array, set header to a pyfits header type")
data = hdu
else:
raise SculptArgumentError('hdu', "can only be one of pyfits.PrimaryHDU type or numpy ndarray")
hdr = header.copy()
dt = data.copy()
hdu = pyfits.PrimaryHDU(dt, header=hdr)
if gauss_width <= 0 or type(gauss_width) != types.IntType:
raise SculptArgumentError('gauss_width', "should be positive and non-zero integer")
try:
if len(p1) != 2 and len(p2) != 2:
raise SculptArgumentError('positions', "Positions p1 and p2 should be 2-element tuples, lists or arrays")
except:
raise SculptArgumentError('positions', "Positions p1 and p2 should be 2-element tuples, lists or arrays")
x1, y1 = p1
x2, y2 = p2
m = (y1-y2)/(x1-x2) #slope of line
d = math.sqrt((x1-x2)**2 + (y1-y2)**2.)
posvel = numpy.zeros((int(d), dt.shape[2]), dtype='float')
dist = numpy.arange(int(d))
if x1 <= x2:
x = x1 + numpy.sqrt(dist**2./(1+m**2.)) #2nd term is deltax
else:
x = x1 - numpy.sqrt(dist**2./(1+m**2.)) #2nd term is deltax
y = y1 + m*(x-x1)
for i in range(int(d)):
posvel[i,:] = extract_spec(hdu, x[i], y[i],
gauss_width=gauss_width).data
xmid = (x1+x2)/2.
ymid = (y1+y2)/2.
r, d = xyad(header, xmid, ymid)
sxaddpar(hdr, "CRVAL2", r)
mid = posvel.shape[0]/2.
sxaddpar(hdr, "CRPIX2", mid)
sxaddpar(hdr, "NAXIS", 2)
sxdelpar(hdr, "NAXIS3")
for name in ('CTYPE', 'CRVAL', 'CDELT', 'CRPIX'):
sxdelpar(hdr, "%s3" % name)
sxaddhist(hdr, "Extracted posvel image from (%.1f, %.1f) to (%.1f, %.1f) with gauss_width=%s" % (x1, y1, x2, y2, gauss_width))
return pyfits.PrimaryHDU(posvel, header=hdr)