pi = np.pi
e = np.e
plt.close('all')
c = 3. * 10**8
h = 6.62 * 10**-34
k = 1.38 * 10**-23
Ken98 = (4.5 * 10**-44)
Conversion2Chabrier = 1.7 # Also Madau
Calzetti12 = 2.8 * 10**-44
arrow = u'$\u2193$'
PATH = '/Users/jansen/Google Drive/Astro/'
fsz = gst.graph_format()
New = Table.read(PATH + 'Four_Quasars/Four_Quasars.fits')
import Plotting_tools as emplot
def smooth(image, sm):
from astropy.convolution import Gaussian2DKernel
from scipy.signal import convolve as scipy_convolve
from astropy.convolution import convolve
gauss_kernel = Gaussian2DKernel(sm)
con_im = convolve(image, gauss_kernel)
pi = np.pi
e = np.e
plt.close('all')
c = 3. * 10**8
h = 6.62 * 10**-34
k = 1.38 * 10**-23
Ken98 = (4.5 * 10**-44)
Conversion2Chabrier = 1.7 # Also Madau
Calzetti12 = 2.8 * 10**-44
arrow = u'$\u2193$'
PATH = '/Users/jansen/Google Drive/Astro/'
fsz = gst.graph_format(Labelsize=15)
def find_nearest(array, value):
array = np.asarray(array)
idx = (np.abs(array - value)).argmin()
return array[idx]
def find_nearest_idx(array, value):
array = np.asarray(array)
idx = (np.abs(array - value)).argmin()
return idx
def gauss(x, k, sig):