def survey_footprint(ax, survey_filename, FoV):
''' This function plots the survey footprint map on the given matplotlib
axes instance
Input
-----
ax : matplotlib axes instance
The axes instance to plot the footprint map to
survey_filename : string
The path to the survey file
'''
survey = np.loadtxt(survey_filename)
x_min = -FoV[0] / 2
y_min = -FoV[1] / 2
x_max = FoV[0] / 2
y_max = FoV[1] / 2
x = np.array([x_min, x_min, x_max, x_max, x_min])
y = np.array([y_min, y_max, y_max, y_min, y_min])
for image in survey:
alpha, beta = transformations.fp2sky(x, y, image[1:3], image[3])
ax.plot(alpha, beta, 'k-', alpha=0.5)
return None
def survey_footprint(ax, survey_filename, FoV):
''' This function plots the survey footprint map on the given matplotlib
axes instance
Input
-----
ax : matplotlib axes instance
The axes instance to plot the footprint map to
survey_filename : string
The path to the survey file
'''
survey = np.loadtxt(survey_filename)
x_min = -FoV[0] / 2
y_min = -FoV[1] / 2
x_max = FoV[0] / 2
y_max = FoV[1] / 2
x = np.array([x_min, x_min, x_max, x_max, x_min])
y = np.array([y_min, y_max, y_max, y_min, y_min])
for image in survey:
alpha, beta = transformations.fp2sky(x, y, image[1:3], image[3])
ax.plot(alpha, beta, 'k-', alpha=0.5)
return None
def camera(data_dir, sky_catalog, measured_catalog, FoV,
pointing, orientation, verbose=False):
''' Saves out a single camera exposure, along with the total sky catalog
and the meas
Parameters
----------
data_dir : string
The output directory
sky_catalog : object
Object of the sky catalog (*.ID, *.mag, *.alpha, *.beta, *.size)
measured_catalog : object
Object of measured sources on focal plane in a single pointing
(*.size, *.ID, *.x, *.y, *true_invvar, *.counts, *.invvar)
FoV : float array
The imagers field-of-view in degrees (dalpha, dbeta)
pointing : np.array
Array of telescope pointing (alpha, beta)
orientation : float
Rotation of the telescope
verbose : boolean
True to run function in verbose mode
'''
filename = '{0}/camera_image.p'.format(data_dir)
if verbose:
print("Saving out camera image to {0}...".format(filename))
x = 0.5 * np.array([-FoV[0], -FoV[0], FoV[0], FoV[0], -FoV[0]])
y = 0.5 * np.array([-FoV[1], FoV[1], FoV[1], -FoV[1], -FoV[1]])
alpha, beta = transformations.fp2sky(x, y, pointing, orientation)
dic = {'sources_x': measured_catalog.x,
'sources_y': measured_catalog.y,
'sky_catalog': sky_catalog,
'pointing': pointing,
'orientation': orientation,
'fp_x': x,
'fp_y': y,
'fp_alpha': alpha,
'fp_beta': beta}
pickle.dump(dic, open(filename, "wb"))
if verbose:
print("...done!")
fig.text(0.025, 0.5, r'Sky Position $\beta$ (deg$^2$)',
va='center', ha='center', rotation=90)
for indx in range(len(dirs)):
params = pickle.load(open('{0}/parameters.p'.format(dirs[indx])))
FoV = params['FoV']
sky_limits = params['sky_limits']
x = 0.5 * np.array([-FoV[0], -FoV[0], FoV[0], FoV[0], -FoV[0]])
y = 0.5 * np.array([-FoV[1], FoV[1], FoV[1], -FoV[1], -FoV[1]])
survey = np.loadtxt((dirs[indx] + '/survey.txt'))
for image in survey:
alpha, beta = transformations.fp2sky(x, y, image[1:3], image[3])
ax[indx].plot(alpha, beta, 'k-', alpha=0.4)
min_sky = np.min(sky_limits) \
- 0.02 * (np.max(sky_limits) - np.min(sky_limits))
max_sky = np.max(sky_limits) \
+ 0.02 * (np.max(sky_limits) - np.min(sky_limits))
ax[indx].set_xlim(min_sky, max_sky)
ax[indx].set_ylim(min_sky, max_sky)
ax[0].text(0.95, 0.04, 'A', va='center', ha='center',
transform=ax[0].transAxes)
ax[1].text(0.05, 0.04, 'B', va='center', ha='center',
transform=ax[1].transAxes)
ax[2].text(0.95, 0.96, 'C', va='center', ha='center',
transform=ax[2].transAxes)