Example #1
0
historical = 'c_XU' in data_table.colnames

############################################################################
############ COMPONENT OVERLAPS ############################################
############################################################################

print('Create data dict')
# Create data dict
data_dict = tabletool.build_data_dict_from_table(
    data_table,
    get_background_overlaps=True,
    historical=historical,
)

# Create components
comps = SphereComponent.load_raw_components(comps_filename)

# COMPONENT OVERLAPS
overlaps = expectmax.get_all_lnoverlaps(data_dict, comps)
print('overlaps.shape', overlaps.shape, len(comps))

# MEMBERSHIP PROBABILITIES
membership_probabilities = np.array(
    [expectmax.calc_membership_probs(ol) for ol in overlaps])

# Create a table
for i in range(membership_probabilities.shape[1] - 1):
    data_table['membership_%d' % (i + 1)] = membership_probabilities[:, i]
data_table['membership_bg'] = membership_probabilities[:, -1]

# Print data
Example #2
0
        return recent_lims
    else:
        try:
            return [np.min((current_lims[0], recent_lims[0])),
                    np.max((current_lims[1], recent_lims[1]))]
        except:
            import pdb; pdb.set_trace()


labels = 'XYZUVW'
units = 3*['pc'] + 3*['km/s']
plt_dir = '../plots/scocen_formation/'
all_comps_file = '../results/all_nonbg_scocen_comps.npy'

# Reading in and tidying components
all_comps = SphereComponent.load_raw_components(all_comps_file)

# # Pop off some manually identified duplicates
# all_comps.pop(9)
# all_comps.pop(6)

print('ages of components: {}'.format([c.get_age() for c in all_comps]))

max_age = np.max([c.get_age() for c in all_comps])

ntimes = 100
times = np.linspace(max_age, 0, ntimes)

#for time in times:

time_ix = ntimes - ntimes/2
Example #3
0
"""

import numpy as np
import sys

sys.path.insert(0, '..')
from chronostar.component import SphereComponent
from chronostar import tabletool
from chronostar import expectmax
from astropy.table import Table, vstack, join

# Create components
#c = np.load('all_nonbg_scocen_comps.npy') # including LCC
#comps = [SphereComponent(pars=x) for x in c]
comps = SphereComponent.load_raw_components('all_nonbg_scocen_comps.npy')
print('components', c.shape)
print('Are there duplicate components?')

#datafile = 'data_table_cartesian_with_bg_ols.fits'
datafile = 'data_table_cartesian_including_tims_stars_with_bg_ols.fits'

# Read Gaia data including both stars with known and missing radial velocities
#datafile = 'data_table_cartesian_100k.fits'
data_table = tabletool.read(datafile)

# This table is masked. Unmask:
data_table = data_table.filled()

print('DATA READ', len(data_table))
historical = 'c_XU' in data_table.colnames
'''
Noticed issue with calculating a component's current
day mean. Behaviour of trace_cartesian_orbit varies based
on whether a single age is provided vs a range of times
'''

import numpy as np
import sys

sys.path.insert(0, '..')
from chronostar.component import SphereComponent
from chronostar.traceorbit import trace_cartesian_orbit

bugged_comp = SphereComponent.load_raw_components('bugged_component.npy')[0]

y_pos_now = bugged_comp.get_mean_now()[1]
print('Mean then: {}'.format(bugged_comp.get_mean()))
print('Internally calculated mean_now: {}'.format(bugged_comp.get_mean_now()))
mean_then = bugged_comp.get_mean()
age = bugged_comp.get_age()
y_pos_linear = mean_then[1] + mean_then[4] * age
print('Linear Y motion: {}'.format(y_pos_linear))

print('Difference of {}'.format(y_pos_now - y_pos_linear))

ts = np.linspace(0, bugged_comp.get_age(), 50)
for method in [
        'odeint',
        'symplec4_c',
        'rk4_c',
        'dopr54_c',
Example #5
0
# Initialise all stars in dataset to be full members of first component
using_bg = config.config.get('include_background_distribution', False)
init_memb_probs = np.zeros((len(data_dict['means']), 1 + using_bg))
init_memb_probs[:, 0] = 1.

store_burnin_chains = config.advanced.get('store_burnin_chains', False)
if store_burnin_chains:
    log_message(msg='Storing burnin chains', symbol='-')

# Try and recover any results from previous run
try:
    prev_med_and_spans = np.load(run_dir + 'final/' + final_med_and_spans_file)
    prev_memb_probs = np.load(run_dir + 'final/' + final_memb_probs_file)
    try:
        prev_comps = Component.load_raw_components(
            str(run_dir + 'final/' + final_comps_file))
    # Final comps are there, they just can't be read by current module
    # so quickly fit them based on fixed prev membership probabilities
    except AttributeError:
        logging.info('Component class has been modified, reconstructing '
                     'from chain')
        prev_comps = ncomps * [None]
        for i in range(ncomps):
            final_cdir = run_dir + 'final/comp{}/'.format(i)
            chain = np.load(final_cdir + 'final_chain.npy')
            lnprob = np.load(final_cdir + 'final_lnprob.npy')
            npars = len(Component.PARAMETER_FORMAT)
            best_ix = np.argmax(lnprob)
            best_pars = chain.reshape(-1, npars)[best_ix]
            prev_comps[i] = Component(emcee_pars=best_pars)
        Component.store_raw_components(
if PLOT_BPMG_REAL:
    # PLOTTING ITERATION 6E
    # star_pars_file = '../../data/beta_Pictoris_with_gaia_small_xyzuvw.fits'
    table_file = '../../data/paper1/beta_Pictoris_corrected_everything.fits'
    bpmg_table = Table.read(table_file)
    star_pars, table_ixs = tabletool.build_data_dict_from_table(
        bpmg_table, return_table_ixs=True)
    nstars = len(table_ixs[0])
    fit_name = 'bpmg_and_nearby'
    rdir = '../../results/beta_Pictoris_with_gaia_small_inv2/6/E/final/'

    memb_file = rdir + 'final_membership.npy'
    comp_file = rdir + 'final_comps.npy'

    z = np.load(memb_file)
    comps = SphereComponent.load_raw_components(comp_file)

    # Assign markers based on BANYAN membership
    banyan_markers = np.array(nstars * ['.'])
    banyan_membs = bpmg_table['banyan_assoc'][table_ixs]

    # Assign markers to each star (via `banyan_markers`) whilst concurrently
    # building list of maker style and the corresponding association for legend
    marker_style = []
    marker_label = []
    banyan_memb_set = set(banyan_membs)
    for bassoc in banyan_memb_set:
        if bassoc not in acronyms.keys():
            acronyms[bassoc] = bassoc
    # Do BPMG manually
    banyan_markers[np.where(banyan_membs == 'beta Pictoris')] = 'v'
Example #7
0
"""
Temporary script which aids in the loading and
analysis of BPMG 6E fit
"""
import numpy as np

from astropy.table import Table

import sys
sys.path.insert(0, '..')
from chronostar import tabletool
from chronostar.component import SphereComponent

master_table_file = '../data/paper1/beta_Pictoris_corrected_everything.fits'

bpmg_rdir = '../results/beta_Pictoris_with_gaia_small_inv2/'

fz = np.load(bpmg_rdir + 'final_membership.npy')
fcomps = SphereComponent.load_raw_components(bpmg_rdir + 'final_comps.npy')
fmers = np.load(bpmg_rdir + 'final_med_errs.npy')

master_table = Table.read(master_table_file)
star_pars, table_ixs = tabletool.build_data_dict_from_table(
    master_table, return_table_ixs=True)

old_table_file = '../data/paper1/beta_Pictoris_with_gaia_small_everything_final.fits'
old_table = Table.read(old_table_file)