def plot_doc():
"""
"""
img = xFITSImage(os.path.join(XIMPOL_DATA, 'crab_complex_cmap.fits'))
fig = img.plot(show=False)
xFITSImage.add_label(fig, 'XIPE %d ks' %DURATION/1000.)
plt.show()
def plot_doc():
"""
"""
img = xFITSImage(os.path.join(XIMPOL_DATA, 'tycho_cmap.fits'))
fig = img.plot(show=False)
xFITSImage.add_label(fig, 'XIPE 300 ks')
plt.show()
def test_vignetting(self):
"""
"""
from ximpol import XIMPOL_CONFIG
file_path = os.path.join(XIMPOL_CONFIG, 'fits', 'casa_1p5_3p0_keV.fits')
aeff = load_arf(DEFAULT_IRF_NAME)
image = xFITSImage(file_path)
def plot_doc():
"""
"""
img = xFITSImage(os.path.join(XIMPOL_DATA, 'tycho_cmap.fits'))
fig = img.plot(show=False)
xFITSImage.add_label(fig, 'XIPE 300 ks')
plt.show()
def plot_ymap(self, overlay=True):
"""Plot the y polarization map.
"""
if self.y_img is None:
self.y_img = xFITSImage(self.ymap_file_path, build_cdf=False)
fig = self.y_img.plot(show=False)
if overlay:
self.overlay_arrows(fig)
return fig
def plot_ymap(self, overlay=True):
"""Plot the y polarization map.
"""
if self.y_img is None:
self.y_img = xFITSImage(self.ymap_file_path, build_cdf=False)
fig = self.y_img.plot(show=False)
if overlay:
self.overlay_arrows(fig)
return fig
def plot_ymap(self, overlay=True, show=False):
"""Plot the y polarization map.
"""
if self.y_img is None:
self.y_img = xFITSImage(self.ymap_file_path, build_cdf=False)
fig = self.y_img.plot(show=False, zlabel="Polarization degree (y)")
if overlay:
self.overlay_arrows(fig)
if show:
plt.show()
return fig
def plot_doc():
"""
"""
img = xFITSImage(os.path.join(XIMPOL_DATA, 'casa_cmap.fits'))
fig = img.plot(show=False)
#Option to draw the psf circle on the count map
RAD_PSF = 11/60.
fig.show_circles(350.769, 58.873, RAD_PSF/60., lw=2, color='white')
fig.add_label(0.73,0.90, 'PSF', relative=True, size='x-large',
color='white', horizontalalignment='left')
xFITSImage.add_label(fig, 'XIPE 250 ks')
plt.show()
def __init__(self, name, img_file_path, energy_spectrum,
polarization_degree, polarization_angle, column_density=0.,
redshift=0., min_validity_time=0.,
max_validity_time=DEFAULT_MAX_VALIDITY_TIME, identifier=None):
"""Constructor.
"""
xModelComponentBase.__init__(self, name, energy_spectrum,
polarization_degree, polarization_angle,
column_density, redshift,
min_validity_time, max_validity_time,
identifier)
self.image = xFITSImage(img_file_path)
def plot_polarization_degree(self, show=True):
"""
"""
import aplpy
if self.x_img is None:
self.x_img = xFITSImage(self.xmap_file_path, build_cdf=False)
if self.y_img is None:
self.y_img = xFITSImage(self.ymap_file_path, build_cdf=False)
_data = numpy.sqrt(self.x_data ** 2 + self.y_data ** 2)
hdu_list = [self.x_img.hdu_list[0].copy()]
hdu_list[0].data = _data
with context_no_grids():
fig = aplpy.FITSFigure(hdu_list[0], figure=plt.figure())
fig.add_grid()
fig.show_colorscale(cmap="afmhot", vmin=None, vmax=None)
fig.add_colorbar()
fig.colorbar.set_axis_label_text("Polarization degree")
if show:
plt.show()
return fig
def display():
"""Display the source model.
"""
from ximpol.utils.matplotlib_ import pyplot as plt
from ximpol.srcmodel.img import xFITSImage
print(ROI_MODEL)
fig = plt.figure('Energy spectrum')
spectral_model_spline.plot(logy=True, show=False, label='Total')
img = xFITSImage(img_file_path)
img.plot(show=False)
plt.show()
def plot(cmap_file):
full_map = xBinnedMap(cmap_file)
fig = full_map.plot(show=False)
# fig.show_circles(RA, DEC, RAD/60., lw=1)
fig.show_circles(RA_CORE, DEC_CORE, RAD_PSF / 60.0, lw=1, color="white")
fig.show_circles(RA_JET, DEC_JET, RAD_PSF / 60.0, lw=1, color="white")
fig.recenter(RA + 0.003, DEC, 1 / 60.0)
fig.show_colorscale(stretch="linear", cmap="afmhot", vmin=80, vmax=1500)
fig.add_label(0.1, 0.9, "XIPE 2 Ms", relative=True, size="xx-large", color="white", horizontalalignment="left")
image = xFITSImage(IMAGE_FITS_PATH, build_cdf=False)
fig2 = image.plot(show=False)
fig2.recenter(RA + 0.003, DEC, 1 / 60.0)
fig2.show_colorscale(stretch="log", cmap="afmhot", vmin=2, vmax=200)
fig2.add_label(
0.1, 0.9, "Chandra 39.5 ks", relative=True, size="xx-large", color="white", horizontalalignment="left"
)
fig.show_contour(IMAGE_FITS_PATH, levels=[6, 10, 20, 50, 100], colors="green", smooth=3)
def display():
"""Display the source model.
"""
from ximpol.utils.matplotlib_ import pyplot as plt
from ximpol.srcmodel.img import xFITSImage
print(ROI_MODEL)
fig = plt.figure('Energy spectrum')
total_spectral_model.plot(logy=True, show=False, label='Total')
nonthermal_spectral_model.plot(logy=True, show=False, label='Non-thermal')
thermal_spectral_model.plot(logy=True, show=False, label='Thermal')
plt.legend(bbox_to_anchor=(0.95, 0.95))
fig = thermal_component.image.plot(show=False)
xFITSImage.add_label(fig, 'Chandra 1.5-3.0 keV')
fig = nonthermal_component.image.plot(show=False)
xFITSImage.add_label(fig, 'Chandra 4.0-6.0 keV')
img = xFITSImage(he_img_file_path)
fig = img.plot(show=False)
polarization_map.build_grid_sample(ROI_MODEL.ra, ROI_MODEL.dec)
polarization_map.overlay_arrows(fig)
plt.show()
def display():
"""Display the source model.
"""
from ximpol.utils.matplotlib_ import pyplot as plt
from ximpol.srcmodel.img import xFITSImage
print(ROI_MODEL)
fig = plt.figure('Energy spectrum')
total_spectral_model.plot(logy=True, show=False, label='Total')
nonthermal_spectral_model.plot(logy=True, show=False, label='Non-thermal')
thermal_spectral_model.plot(logy=True, show=False, label='Thermal')
plt.legend(bbox_to_anchor=(0.95, 0.95))
fig = thermal_component.image.plot(show=False)
xFITSImage.add_label(fig, 'Chandra 1.5-3.0 keV')
fig = nonthermal_component.image.plot(show=False)
xFITSImage.add_label(fig, 'Chandra 4.0-6.0 keV')
img = xFITSImage(he_img_file_path)
fig = img.plot(show=False)
polarization_map.build_grid_sample(ROI_MODEL.ra, ROI_MODEL.dec)
polarization_map.overlay_arrows(fig)
plt.show()
def display():
"""Display the source model.
"""
from ximpol.utils.matplotlib_ import pyplot as plt
from ximpol.srcmodel.img import xFITSImage
print(ROI_MODEL)
#fig = plt.figure('Energy spectrum')
#for src in ROI_MODEL.values():
#src.energy_spectrum.plot(logy=True, show=False, label=src.name)
#plt.legend(bbox_to_anchor=(0.95, 0.95))
# fig = thermal_component.image.plot(show=False)
#xFITSImage.add_label(fig, 'Chandra 1.5-3.0 keV')
#fig = nonthermal_component.image.plot(show=False)
#xFITSImage.add_label(fig, 'Chandra 4.0-6.0 keV')
img = xFITSImage(img_file_path)
fig = img.plot(show=False)
for polarization_map in polarization_maps:
polarization_map.build_grid_sample(ROI_MODEL.ra, ROI_MODEL.dec,num_points=100)
polarization_map.overlay_arrows(fig)
plt.show()
self.overlay_arrows(fig)
return fig
def plot_ymap(self, overlay=True):
"""Plot the y polarization map.
"""
if self.y_img is None:
self.y_img = xFITSImage(self.ymap_file_path, build_cdf=False)
fig = self.y_img.plot(show=False)
if overlay:
self.overlay_arrows(fig)
return fig
if __name__ == '__main__':
import os
from ximpol import XIMPOL_CONFIG
from ximpol.utils.matplotlib_ import pyplot as plt
file_path_x = os.path.join(XIMPOL_CONFIG, 'fits', 'casa_pol_x.fits')
file_path_y = os.path.join(XIMPOL_CONFIG, 'fits', 'casa_pol_y.fits')
img_file_path = os.path.join(XIMPOL_CONFIG, 'fits',
'casa_1p5_3p0_keV.fits')
polarization_map = xPolarizationMap(file_path_x, file_path_y)
polarization_map.build_grid_sample(350.863, 58.815)
polarization_map.plot_xmap()
polarization_map.plot_ymap()
img = xFITSImage(img_file_path)
fig = img.plot(show=False)
polarization_map.overlay_arrows(fig)
plt.show()
if degrees:
_data = numpy.degrees(_data)
hdu_list = [self.x_img.hdu_list[0].copy()]
hdu_list[0].data = _data
with context_no_grids():
fig = aplpy.FITSFigure(hdu_list[0], figure=plt.figure())
fig.add_grid()
fig.show_colorscale(cmap="afmhot", vmin=None, vmax=None)
fig.add_colorbar()
fig.colorbar.set_axis_label_text("Polarization angle")
if show:
plt.show()
return fig
if __name__ == "__main__":
import os
from ximpol import XIMPOL_CONFIG
file_path_x = os.path.join(XIMPOL_CONFIG, "fits", "casa_pol_x.fits")
file_path_y = os.path.join(XIMPOL_CONFIG, "fits", "casa_pol_y.fits")
img_file_path = os.path.join(XIMPOL_CONFIG, "fits", "casa_1p5_3p0_keV.fits")
polarization_map = xPolarizationMap(file_path_x, file_path_y)
polarization_map.build_grid_sample(350.863, 58.815)
polarization_map.plot_xmap()
polarization_map.plot_ymap()
img = xFITSImage(img_file_path)
fig = img.plot(show=False)
polarization_map.overlay_arrows(fig)
plt.show()
def __init__(self, file_path):
"""Constructor.
"""
self.image = xFITSImage(file_path, build_cdf=False)
def __init__(self, file_path):
"""Constructor.
"""
self.image = xFITSImage(file_path, build_cdf=False)
