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:
