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
