class GPSFermiPlot(GalacticPlaneSurveyPanelPlot):
def main(self, figure, subplot):
filename = FermiGalacticCenter.filenames()['counts']
self.fits_figure = FITSFigure(filename, figure=figure, subplot=subplot)
self.fits_figure.show_colorscale(vmin=1, vmax=10)
self.fits_figure.ticks.set_xspacing(2)
def test_scalebar_length():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_scalebar(0.1)
f.scalebar.set_length(0.01)
f.scalebar.set_length(0.1)
f.close()
def test_frame_linewidth():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.frame.set_linewidth(0)
f.frame.set_linewidth(1)
f.frame.set_linewidth(10)
f.close()
def test_scalebar_showhide():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_scalebar(0.1)
f.scalebar.hide()
f.scalebar.show(0.1)
f.close()
def test_scalebar_font():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_scalebar(0.1)
f.scalebar.set_font(size='small', weight='bold', stretch='normal',
family='serif', style='normal', variant='normal')
f.close()
def test_scalebar_frame():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_scalebar(0.1)
f.scalebar.set_frame(True)
f.scalebar.set_frame(False)
f.close()
def test_ticks_minor_frequency():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.ticks.set_minor_frequency(1)
f.ticks.set_minor_frequency(5)
f.ticks.set_minor_frequency(10)
f.close()
def test_ticks_linewidth():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.ticks.set_linewidth(1)
f.ticks.set_linewidth(3)
f.ticks.set_linewidth(10)
f.close()
def test_ticks_color():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.ticks.set_color('black')
f.ticks.set_color('#003344')
f.ticks.set_color((1.0, 0.4, 0.3))
f.close()
def test_grid_addremove():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_grid()
f.remove_grid()
f.add_grid()
f.close()
def test_scalebar_addremove():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_scalebar(0.1)
f.remove_scalebar()
f.add_scalebar(0.1)
f.close()
def part_8():
object_list = ['ROXs12','ROXs42B','ROXs42B']
filename_list = ['ROXs12','ROXs42Bb','ROXs42Bc']
for i in range(len(filename_list)):
outfile = open('position_'+filename_list[i]+'.dat','w')
outfile.write('# '+'%25s'%'file name\t'\
+'%12s'%'x planet\t'\
+'%12s'%'y planet\t'\
+'%12s'%'position angle\t'\
+'%12s'%'projected separation (pixels)\n')
if filename_list[i] == 'ROXs12': int_x,int_y = 562,685
elif filename_list[i] == 'ROXs42Bb': int_x,int_y = 629,495
elif filename_list[i] == 'ROXs42Bc': int_x,int_y = 546,465
parts = ['','_CMsub','_ADIsub','_bPSFsub']
for j in parts:
filename = object_list[i]+j+'_aligned_median.fits'
fit_radius = 16
f = fits.open(filename)
scidata = f[0].data
x_data = scidata[int_y,int_x-fit_radius:int_x+fit_radius+1]
x_data -= min(x_data)
fit_x = np.linspace(-fit_radius,fit_radius,1+2*fit_radius)
xfitParam, xfitCovar = curve_fit(gaussian_pdf,fit_x,x_data)
y_data = scidata[int_y-fit_radius:int_y+fit_radius+1,int_x]
y_data -= min(y_data)
fit_y = np.linspace(-fit_radius,fit_radius,1+2*fit_radius)
yfitParam, yfitCovar = curve_fit(gaussian_pdf,fit_y,y_data)
thisPARANG = f[0].header['PARANG']
thisROTPPOSN = f[0].header['ROTPPOSN']
thisEL = f[0].header['EL']
thisINSTANGL = f[0].header['INSTANGL']
PA_yaxis = thisPARANG +thisROTPPOSN -thisEL -thisINSTANGL
PA_planet = PA_yaxis -rad_to_deg(arctan2(float(xfitParam[0]+int_x-512),float(yfitParam[0]+int_y-512)))
if PA_planet < 0: PA_planet += 360
outfile.write('%25s'%str(object_list[i]+j+'_aligned_median.fits')+'\t'\
+'%8s'%'%.3f'%(float(xfitParam[0]+int_x))+'\t'\
+'%8s'%'%.3f'%(float(yfitParam[0]+int_y))+'\t'\
+'%8s'%'%.3f'%(float(PA_planet))+'\t'\
+'%8s'%'%.3f'%(float(sqrt((xfitParam[0]+int_x-512)**2+(yfitParam[0]+int_y-512)**2)))+'\n')
tf = FITSFigure(filename)
tf.show_colorscale(cmap='gray')
tf.add_colorbar()
tf.colorbar.show(location='top',box_orientation='horizontal')
plt.savefig(object_list[i]+j+'_aligned_median.pdf',dpi=200)
plt.close()
outfile.close()
def test_scalebar_corner():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_scalebar(0.1)
for corner in ['top', 'bottom', 'left', 'right', 'top left', 'top right',
'bottom left', 'bottom right']:
f.scalebar.set_corner(corner)
f.close()
def test_tick_labels_position():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.tick_labels.set_xposition('top')
f.tick_labels.set_xposition('bottom')
f.tick_labels.set_yposition('right')
f.tick_labels.set_yposition('left')
f.close()
def test_beam_linestyle():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_beam(major=0.1, minor=0.04, angle=10.)
f.beam.set_linestyle('solid')
f.beam.set_linestyle('dotted')
f.beam.set_linestyle('dashed')
f.close()
def test_axis_labels_position():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.axis_labels.set_xposition('top')
f.axis_labels.set_xposition('bottom')
f.axis_labels.set_yposition('right')
f.axis_labels.set_yposition('left')
f.close()
def test_beam_edgecolor():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_beam(major=0.1, minor=0.04, angle=10.)
f.beam.set_edgecolor('black')
f.beam.set_edgecolor('#003344')
f.beam.set_edgecolor((1.0, 0.4, 0.3))
f.close()
def test_scalebar_alpha():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_scalebar(0.1)
f.scalebar.set_alpha(0.1)
f.scalebar.set_alpha(0.2)
f.scalebar.set_alpha(0.5)
f.close()
def test_grid_color():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_grid()
f.grid.set_color('black')
f.grid.set_color('#003344')
f.grid.set_color((1.0, 0.4, 0.3))
f.close()
def test_grid_alpha():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_grid()
f.grid.set_alpha(0.0)
f.grid.set_alpha(0.3)
f.grid.set_alpha(1.0)
f.close()
def test_scalebar_color():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_scalebar(0.1)
f.scalebar.set_color('black')
f.scalebar.set_color('#003344')
f.scalebar.set_color((1.0, 0.4, 0.3))
f.close()
def test_beam_linewidth():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_beam(major=0.1, minor=0.04, angle=10.)
f.beam.set_linewidth(0)
f.beam.set_linewidth(1)
f.beam.set_linewidth(5)
f.close()
def test_scalebar_label():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_scalebar(0.1)
f.scalebar.set_label('1 pc')
f.scalebar.set_label('5 AU')
f.scalebar.set_label('2"')
f.close()
def main(self, figure, subplot):
filename = FermiGalacticCenter.filenames()['counts']
self.fits_figure = FITSFigure(filename,
hdu=1,
figure=figure,
subplot=subplot)
self.fits_figure.show_colorscale(vmin=1, vmax=10, cmap='afmhot')
self.fits_figure.ticks.set_xspacing(2)
def test_grid_linestyle():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_grid()
f.grid.set_linestyle('solid')
f.grid.set_linestyle('dashed')
f.grid.set_linestyle('dotted')
f.close()
def test_grid_linewidth():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_grid()
f.grid.set_linewidth(0)
f.grid.set_linewidth(2)
f.grid.set_linewidth(5)
f.close()
def test_ticks_spacing():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.ticks.set_xspacing(0.5)
f.ticks.set_xspacing(1.)
f.ticks.set_yspacing(0.5)
f.ticks.set_yspacing(1.)
f.close()
def test_beam_corner():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_beam(major=0.1, minor=0.04, angle=10.)
for corner in ['top', 'bottom', 'left', 'right', 'top left', 'top right',
'bottom left', 'bottom right']:
f.beam.set_corner(corner)
f.close()
def test_init_extensive_wcs(header, dimensions):
hdu = generate_hdu(header)
if 'CAR' in header:
f = FITSFigure(hdu, dimensions=dimensions, convention='calabretta')
else:
f = FITSFigure(hdu, dimensions=dimensions)
f.show_grayscale()
f.add_grid()
f.close()
def fits_to_png(infile, outfile, draw, dpi=100):
"""Plot FITS image in PNG format.
For the default ``dpi=100`` a 1:1 copy of the pixels in the FITS image
and the PNG image is achieved, i.e. they have exactly the same size.
Parameters
----------
infile : str
Input FITS file name
outfile : str
Output PNG file name
draw : callable
Callback function ``draw(figure)``
where ``figure`` is an `~aplpy.FITSFigure`.
dpi : int
Resolution
Examples
--------
>>> def draw(figure):
... x, y, width, height = 42, 0, 3, 2
... figure.recenter(x, y, width, height)
... figure.show_grayscale()
>>> from gammapy.image import fits_to_png
>>> fits_to_png('image.fits', 'image.png', draw)
"""
import matplotlib
matplotlib.use("Agg") # Prevents image popup
import matplotlib.pyplot as plt
from astropy.io import fits
from aplpy import FITSFigure
# Peak ahead just to get the figure size
NAXIS1 = float(fits.getval(infile, "NAXIS1"))
NAXIS2 = float(fits.getval(infile, "NAXIS2"))
# Note: For dpi=100 I get exactly the same FITS and PNG image size in pix.
figsize = np.array((NAXIS1, NAXIS2))
figure = plt.figure(figsize=figsize / dpi)
# Also try this:
# matplotlib.rcParams['figure.figsize'] = NAXIS1, NAXIS2
# figsize(x,y)
subplot = [0, 0, 1, 1]
figure = FITSFigure(infile, figure=figure, subplot=subplot)
draw(figure)
figure.axis_labels.hide()
figure.tick_labels.hide()
figure.ticks.set_linewidth(0)
figure.frame.set_linewidth(0)
figure.save(outfile, max_dpi=dpi, adjust_bbox=False)
def test_axis_labels_show_hide():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.axis_labels.hide()
f.axis_labels.show()
f.axis_labels.hide_x()
f.axis_labels.show_x()
f.axis_labels.hide_y()
f.axis_labels.show_y()
f.close()
def test_ticks_show_hide():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.ticks.hide()
f.ticks.show()
f.ticks.hide_x()
f.ticks.show_x()
f.ticks.hide_y()
f.ticks.show_y()
f.close()
def test_axis_labels_font():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.axis_labels.set_font(size='small',
weight='bold',
stretch='normal',
family='serif',
style='normal',
variant='normal')
f.close()
def fits_to_png(infile, outfile, draw, dpi=100):
"""Plot FITS image in PNG format.
For the default ``dpi=100`` a 1:1 copy of the pixels in the FITS image
and the PNG image is achieved, i.e. they have exactly the same size.
Parameters
----------
infile : str
Input FITS file name
outfile : str
Output PNG file name
draw : callable
Callback function ``draw(figure)``
where ``figure`` is an `~aplpy.FITSFigure`.
dpi : int
Resolution
Examples
--------
>>> def draw(figure):
... x, y, width, height = 42, 0, 3, 2
... figure.recenter(x, y, width, height)
... figure.show_grayscale()
>>> from gammapy.image import fits_to_png
>>> fits_to_png('image.fits', 'image.png', draw)
"""
import matplotlib
matplotlib.use('Agg') # Prevents image popup
import matplotlib.pyplot as plt
from astropy.io import fits
from aplpy import FITSFigure
# Peak ahead just to get the figure size
NAXIS1 = float(fits.getval(infile, 'NAXIS1'))
NAXIS2 = float(fits.getval(infile, 'NAXIS2'))
# Note: For dpi=100 I get exactly the same FITS and PNG image size in pix.
figsize = np.array((NAXIS1, NAXIS2))
figure = plt.figure(figsize=figsize / dpi)
# Also try this:
# matplotlib.rcParams['figure.figsize'] = NAXIS1, NAXIS2
# figsize(x,y)
subplot = [0, 0, 1, 1]
figure = FITSFigure(infile, figure=figure, subplot=subplot)
draw(figure)
figure.axis_labels.hide()
figure.tick_labels.hide()
figure.ticks.set_linewidth(0)
figure.frame.set_linewidth(0)
figure.save(outfile, max_dpi=dpi, adjust_bbox=False)
def test_axis_labels_position_invalid():
data = np.zeros((16, 16))
f = FITSFigure(data)
with pytest.raises(ValueError):
f.axis_labels.set_xposition('right')
with pytest.raises(ValueError):
f.axis_labels.set_xposition('left')
with pytest.raises(ValueError):
f.axis_labels.set_yposition('top')
with pytest.raises(ValueError):
f.axis_labels.set_yposition('bottom')
f.close()
def test_beam_angle():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.show_grayscale()
f.add_beam(major=0.1, minor=0.04, angle=10.)
f.beam.set_angle(0.)
f.beam.set_angle(55.)
f.close()
def test_colorbar_showhide():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.show_grayscale()
f.add_colorbar()
f.colorbar.hide()
f.colorbar.show()
f.close()
def test_colorbar_pad():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.show_grayscale()
f.add_colorbar()
f.colorbar.set_pad(0.1)
f.colorbar.set_pad(0.2)
f.colorbar.set_pad(0.5)
f.close()
def lookAtHDU(hdulist, outputFileName, v1=0, v2=10, channelMode=False, coAddSpectra=False,
lowVelCut = 0, highVelCut = 0, plotInKmPerS = True):
hdu = hdulist[0]
workingHeader = hdu.header
img = momentcube(hdu, v1, v2, moment=0, chan=channelMode)
workingImageHeader = img.header
imglist = pyfits.PrimaryHDU(data=img.data, header=img.header)
# write an output file
hdulist2 = pyfits.hdu
hdulist2 = pyfits.HDUList([imglist])
if os.path.exists(outputFileName):
os.remove(outputFileName)
hdulist2.writeto(outputFileName)
if coAddSpectra:
(axis3Len, axis2Len, specLen) = numpy.shape(hdu.data)
specLen -= lowVelCut
specLen -= highVelCut
meanSpectra = numpy.zeros((specLen))
for axis3Index in range(axis3Len):
for axis2Index in range(axis2Len):
meanSpectra += hdu.data[axis3Index, axis2Index, highVelCut:specLen+highVelCut]
meanSpectra = meanSpectra / float(axis3Len * axis2Len)
vAxisStart = hdu.header['CRVAL1'] - ((hdu.header['CRPIX1'] - 1.0) * hdu.header['CDELT1'])
vAxisEnd = hdu.header['CRVAL1'] + (((specLen + 1) - hdu.header['CRPIX1'] ) * hdu.header['CDELT1'])
vAxisStep = hdu.header['CDELT1']
velocityAxis = numpy.arange(vAxisStart, vAxisEnd, vAxisStep)
if plotInKmPerS:
velocityAxis = velocityAxis / 1000.0
plt.xlabel("Relative Velocity (km/s)")
else:
plt.xlabel("Relative Velocity (m/s)")
velocityAxis = list(velocityAxis)
while specLen < len(velocityAxis):
velocityAxis.pop()
plt.plot(meanSpectra)
# plt.plot(velocityAxis, meanSpectra)
plt.title("max value:" + str(max(meanSpectra)) + " Min value:" + str(min(meanSpectra)))
plt.show()
fig = FITSFigure(img)
fig.show_colorscale( )
# time.sleep(20)
# raw_input('press enter to continue')
return
def test_colorbar_location():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.show_grayscale()
f.add_colorbar()
f.colorbar.set_location('top')
f.colorbar.set_location('bottom')
f.colorbar.set_location('left')
f.colorbar.set_location('right')
f.close()
def test_write_eps(tmpdir, format):
filename = os.path.join(str(tmpdir), 'test_output.eps')
data = np.zeros((16, 16))
f = FITSFigure(data)
f.show_grayscale()
f.save(filename, format=format)
f.close()
if format is None:
assert is_format(filename, 'eps')
else:
assert is_format(filename, format)
def test_write_stringio(tmpdir, format):
s = StringIO()
data = np.zeros((16, 16))
f = FITSFigure(data)
f.show_grayscale()
f.save(s, format=format)
f.close()
s.seek(0)
if format is None:
assert is_format(s, 'png')
else:
assert is_format(s, format)
def test_colorbar_font():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.show_grayscale()
f.add_colorbar()
f.colorbar.set_font(size='small',
weight='bold',
stretch='normal',
family='serif',
style='normal',
variant='normal')
f.close()
def test_beam_hatch():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_beam(major=0.1, minor=0.04, angle=10.)
for hatch in ['/', '\\', '|', '-', '+', 'x', 'o', 'O', '.', '*']:
f.beam.set_hatch(hatch)
f.close()
def test_grid_showhide():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_grid()
f.grid.hide()
f.grid.show()
f.close()
def test_beam_frame():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_beam(major=0.1, minor=0.04, angle=10.)
f.beam.set_frame(True)
f.beam.set_frame(False)
f.close()
def test_scalebar_showhide():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_scalebar(0.1)
f.scalebar.hide()
f.scalebar.show(0.1)
f.close()
def test_scalebar_length():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_scalebar(0.1)
f.scalebar.set_length(0.01)
f.scalebar.set_length(0.1)
f.close()
def test_beam_pad():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_beam(major=0.1, minor=0.04, angle=10.)
f.beam.set_pad(0.1)
f.beam.set_pad(0.3)
f.close()
def test_scalebar_frame():
data = np.zeros((16, 16))
f = FITSFigure(data)
f.add_scalebar(0.1)
f.scalebar.set_frame(True)
f.scalebar.set_frame(False)
f.close()
