if not utils_str.to_float(sys.argv[2]): return False if not utils_str.to_float(sys.argv[3]): return False if not utils_str.to_float(sys.argv[4]): return False return True assert verify_arguments( ), "Usage: found_groups_find_by_avg_pos.py file ra dec radius" input_filename = sys.argv[1] cg = utils_dict.read(input_filename) ra = float(sys.argv[2]) dec = float(sys.argv[3]) radius = float(sys.argv[4]) i_ra = cg["columns"].index("ra") i_dec = cg["columns"].index("dec") groups = cg["groups"] for g in groups: sum_ra = 0 sum_dec = 0 for s in g["stars"]: sum_ra = s[i_ra] sum_dec = s[i_dec]
def verify_arguments(): if len(sys.argv) != 3: return False if not os.path.isfile(sys.argv[1]): return False return True assert verify_arguments( ), "Usage: plot_comoving_groups_against_isochrones.py group_file age" cg = utils_dict.read(sys.argv[1]) age = float(sys.argv[2]) log10_age = numpy.log10(age) isos = {} for i in numpy.arange(0, 4.5, 0.5): iso_path = "isochrones/feh-%.1f.iso.cmd" % i isos[-i] = mist.parse_isochrones(iso_path) cg_cols = cg["columns"] i_teff_cg = cg_cols.index("teff_val") i_lum_cg = cg_cols.index("lum_val") gaia_lteff = [] gaia_lums = []
if len(sys.argv) < 3: return False if not os.path.isfile(sys.argv[1]): return False if not os.path.isfile(sys.argv[2]): return False return True assert verify_arguments(), "Usage: found_groups_combine_with_lamost_dr3.py input_cms input_lamost_csv" input_cms = sys.argv[1] input_lamost_csv = sys.argv[2] cg = utils_dict.read(input_cms) cols = cg["columns"] i_source_id = cols.index("source_id") lamost_cols = ["angDist","_RAJ2000","_DEJ2000","LAMOST","RAJ2000","DEJ2000","Teff","e_Teff","log(g)","e_log(g)","[Fe/H]","e_[Fe/H]","Vmag","gmag","Ksmag","W2mag","r_E(B-V)","E(B-V)","r_pmRA","pmRA","pmDE","RVel","Vphi","Dist","e_Dist","sng","CaHK","Hbeta","Mg2","Mgb","NaD","CEMP","DR4","UCAC4","Link2","Gaia","SDSS","Sloan","2M","ra_epoch2000","dec_epoch2000","errHalfMaj","errHalfMin","errPosAng","source_id","ra","ra_error","dec","dec_error","parallax","parallax_error","pmra","pmra_error","pmdec","pmdec_error","duplicated_source","phot_g_mean_flux","phot_g_mean_flux_error","phot_g_mean_mag","phot_bp_mean_flux","phot_bp_mean_flux_error","phot_bp_mean_mag","phot_rp_mean_flux","phot_rp_mean_flux_error","phot_rp_mean_mag","bp_rp","radial_velocity","radial_velocity_error","rv_nb_transits","teff_val","a_g_val","e_bp_min_rp_val","radius_val","lum_val"] i_source_id_lamost = lamost_cols.index("source_id") lamost_sids = set() csv_fh = open(input_lamost_csv, "r") csv_lines = csv_fh.readlines() csv_fh.close() for i in range(1, len(csv_lines)): # skip header line csv_line = csv_lines[i] if csv_line[0] == "#": continue
# Author: Karl Zylinski, Uppsala University import sys import os import numpy import matplotlib.pyplot as plt import mist import utils_dict cg = utils_dict.read("out_no_groups.cms") cg_cols = cg["columns"] i_teff = cg_cols.index("teff") i_g = cg_cols.index("phot_g_mean_mag") i_dist = cg_cols.index("distance") i_ext = cg_cols.index("a_g_val") i_feh = cg_cols.index("feh") def get_color(feh): if feh < -2: return "red" if feh < -1: return "green" return "gray" def get_size(feh): if feh < -2: return 5 if feh < -1: