def choose_templates(templates, age_lim = 20.0, max_nonzero = 5):
#start out by loading in the template files as a table
import numpy as np
import astropy.table as table
import SPaCT
ssp_rows = []
for template in templates:
template = template.rstrip('.fits').split('/')[1]
spectral_range = template[0]
IMF_type = template[1:3]
IMF_slope = float(template[3:7])
Z = SPaCT.plusminus(template[8])*float(template[9:13])
T = float(template[14:])
#print template + ':', spectral_range, IMF_type, IMF_slope, Z, T
ssp_i = [template, spectral_range, IMF_type, IMF_slope, Z, T]
ssp_rows.append(ssp_i)
ssps = table.Table(map(list, zip(*ssp_rows)), names = ['name', 'spectral range', 'IMF type', 'IMF slope', 'Z', 't'])
ssps = ssps[ssps['t'] <= age_lim]
#then pick up to `max_nonzero` number of templates to be nonzero
nonzero_templates = np.random.choice(ssps['name'], np.random.randint(1, max_nonzero + 1), replace = False)
template_weights = np.random.rand(len(ssps['name'])) * [1. if i in nonzero_templates else 0. for i in ssps['name']]
template_weights /= template_weights.sum()
ssps.add_column(table.Column(name = 'weight', data = template_weights))
return ssps
def simulate_noise(sparse_spectrum, SNR, n_skyfiber_range = [1, 20, 3]):
'''
generate synthetic noise spectra for a given input spectrum, and test the required number of sky fibers (with similar noise profiles) to accurately get the SNR
'''
import numpy as np
import SPaCT
import matplotlib.pyplot as plt
plt.figure(figsize = (6, 4))
for n_skyfibers in range(n_skyfiber_range[0], n_skyfiber_range[1] + 1, n_skyfiber_range[2]):
ifu, galaxy_noise = noisify_ifu(sparse_spectrum, n = n_skyfibers, SNR = SNR)
fiberlist = range(1, n_skyfibers + 1)
SNR_calc = ifu[0] / SPaCT.noise_edgefibers(ifu, width = 3, fiberlist = fiberlist, verbose = False)
bins, edges = np.histogram(SNR_calc, 50, normed = 1)
left, right = edges[:-1],edges[1:]
X = np.array([left,right]).T.flatten()
Y = np.array([bins,bins]).T.flatten()
plt.plot(X, Y/Y.max(), label = str(n_skyfibers) + ' fibers')
plt.axvline(SNR, c = 'k', linestyle = ':')
SNR_annotation = plt.text(SNR, 0.35, '$S/N=' + str(SNR) + '$')
SNR_annotation.set_rotation('vertical')
plt.title('Effect of # of sky fibers on SNR', size = 18)
plt.xscale('log')
plt.ylim([-0.05, 1.05])
plt.xlabel('SNR', size = 18)
plt.ylabel('normed fraction', size = 18)
plt.legend(loc = 'best', prop = {'size':6})
plt.tight_layout()
plt.show()
